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Transcript of DBMS .
• DBMS
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Database trigger Triggers in DBMS
1 Below follows a series of descriptions of how some popular DBMS support triggers.
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Database 1960s Navigational DBMS
1 The introduction of the term database coincided with the availability of direct-access storage (disks and drums) from the mid-1960s onwards. The term represented a contrast with the tape-based systems of the past, allowing shared interactive use rather than daily batch processing. The Oxford English dictionary cites
a 1962 report by the System Development Corporation of California as the first to use the term "data-base" in a specific technical sense.
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Database 1960s Navigational DBMS
1 As computers grew in speed and capability, a number of general-
purpose database systems emerged; by the mid-1960s there were a
number of such systems in commercial use
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Database 1960s Navigational DBMS
1 The Codasyl approach was based on the "manual" navigation of a linked data set which was formed into a
large network
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Database 1960s Navigational DBMS
1 IBM also had their own DBMS system in 1968, known as IMS
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Database 1970s relational DBMS
1 Edgar Codd worked at IBM in San Jose, California, in one of their offshoot offices that was primarily involved in the development of hard disk systems. He was unhappy with the navigational model of the Codasyl approach,
notably the lack of a "search" facility. In 1970, he wrote a number of papers that outlined a new approach to database construction that eventually culminated in the groundbreaking A Relational Model of Data for Large Shared
Data Banks.
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Database 1970s relational DBMS
1 Data may be freely inserted, deleted and edited in these tables, with the DBMS doing whatever maintenance
needed to present a table view to the application/user.
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Database 1970s relational DBMS
1 The relational model also allowed the content of the database to evolve without constant rewriting of links
and pointers
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Database 1970s relational DBMS
1 For instance, a common use of a database system is to track
information about users, their name, login information, various addresses
and phone numbers
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Database 1970s relational DBMS
1 Linking the information back together is the key
to this system
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Database 1970s relational DBMS
1 Just as the navigational approach would require programs to loop in
order to collect records, the relational approach would require loops to
collect information about any one record
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Database 1970s relational DBMS
1 Codd's paper was picked up by two people at Berkeley, Eugene Wong and Michael
Stonebraker
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Database 1970s relational DBMS
1 IBM itself did one test implementation of the relational
model, PRTV, and a production one, Business System 12, both now
discontinued. Honeywell wrote MRDS for Multics, and now there are two
new implementations: Alphora Dataphor and Rel. Most other DBMS
implementations usually called relational are actually SQL DBMSs.
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Database 1970s relational DBMS
1 In 1970, the University of Michigan began development of the MICRO Information
Management System based on D.L. Childs' Set-Theoretic Data model. Micro was used to manage very large data sets by the US
Department of Labor, the U.S. Environmental Protection Agency, and researchers from the
University of Alberta, the University of Michigan, and Wayne State University. It ran on IBM mainframe computers using the Michigan Terminal System. The system remained in
production until 1998.https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Database Late-1970s SQL DBMS
1 IBM started working on a prototype system loosely based on Codd's
concepts as System R in the early 1970s
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Database Late-1970s SQL DBMS
1 Stonebraker went on to apply the lessons from INGRES to develop a new database, Postgres, which is
now known as PostgreSQL. PostgreSQL is often used for global
mission critical applications (the .org and .info domain name registries use it as their primary data store, as do many large companies and financial
institutions).https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Database Late-1970s SQL DBMS
1 In Sweden, Codd's paper was also read and Mimer SQL was developed from the
mid-1970s at Uppsala University. In 1984, this project was consolidated into an independent enterprise. In the early 1980s, Mimer introduced transaction
handling for high robustness in applications, an idea that was
subsequently implemented on most other DBMS.
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Database Late-1970s SQL DBMS
1 Another data model, the entity-relationship model, emerged in 1976 and gained popularity for database
design as it emphasized a more familiar description than the earlier relational model. Later on, entity-
relationship constructs were retrofitted as a data modeling
construct for the relational model, and the difference between the two
have become irrelevant.https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Object database - Comparison with RDBMSs
1 Another benefit of an OODBMS is that it can be programmed with small
procedural differences without affecting the entire system
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Object database - Comparison with RDBMSs
1 Objects don't require assembly and disassembly saving coding time and
execution time to assemble or disassemble objects.
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Object database - Comparison with RDBMSs
1 Better concurrency control - a hierarchy of objects may be
locked.
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Object database - Comparison with RDBMSs
1 Works well for distributed
architectures.
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Object database - Comparison with RDBMSs
1 Less code required when applications are object
oriented.
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Object database - Comparison with RDBMSs
1 Support for RDBMS is more certain and change is less
likely to be required.
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Distributed database - Homogeneous DDBMS
1 In a homogeneous distributed database all sites have identical software and are aware
of each other and agree to cooperate in processing user requests. Each site
surrenders part of its autonomy in terms of right to change schema or software. A
homogeneous DDBMS appears to the user as a single system. The homogeneous system is
much easier to design and manage. The following conditions must be satisfied for
homogeneous database:
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Distributed database - Homogeneous DDBMS
1 The operating system used, at each location must be same or
compatible.[according to whom?][further explanation needed]
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Distributed database - Homogeneous DDBMS
1 The data structures used at each
location must be same or compatible.
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Distributed database - Homogeneous DDBMS
1 The database application (or DBMS) used at each location must be same or compatible.
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Distributed database - Heterogeneous DDBMS
1 On heterogeneous system, translations are required to allow communication between different
sites (or DBMS)
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Database management system - General-purpose and special-purpose DBMSs
1 A common example is an email system: email systems are designed
to optimize the handling of email messages, and do not need
significant portions of a general-purpose DBMS functionality.
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Database management system - General-purpose and special-purpose DBMSs
1 Database designers and database administrators interact with the
DBMS through dedicated interfaces to build and maintain the
applications' databases, and thus need some more knowledge and understanding about how DBMSs operate and the DBMSs' external interfaces and tuning parameters.
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Database management system - General-purpose and special-purpose DBMSs
1 General-purpose databases are usually developed by one
organization or community of programmers, while a different group builds the applications that use it. In
many companies, specialized database administrators maintain databases, run reports, and may
work on code that runs on the databases themselves (rather than in
the client application).https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Database management system - 1960s Navigational DBMS
1 The Codasyl approach was based on the manual navigation of a linked data set which was formed into a
large network
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Database management system - 1960s Navigational DBMS
1 International Business Machines|IBM also had their own DBMS system in 1968, known as
IMS
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Database management system - 1970s relational DBMS
1 Edgar Codd worked at International Business Machines|IBM in San Jose, California, in one of their offshoot
offices that was primarily involved in the development of hard disk
systems
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Database management system - 1970s relational DBMS
1 Data may be freely inserted, deleted and edited in these tables, with the DBMS doing whatever maintenance
needed to present a table view to the application/user.
https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Database management system - 1970s relational DBMS
1 Linking the information back together is the key
to this system
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Database management system - 1970s relational DBMS
1 IBM itself did one test implementation of the relational
model, PRTV, and a production one, Business System 12, both now discontinued. Honeywell wrote
Multics Relational Data Store|MRDS for Multics, and now there are two new implementations: Dataphor|
Alphora Dataphor and Rel (DBMS)|Rel. Most other DBMS
implementations usually called relational are actually SQL DBMSs.
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Database management system - 1970s relational DBMS
1 In 1970, the University of Michigan began development of the MICRO
Information Management SystemWilliam Hershey and Carol Easthope, , Spring Joint Computer
Conference, May 1972 in ACM SIGIR Forum, Volume 7, Issue 4 (December
1972), pp
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Database management system - Late-1970s SQL DBMS
1 IBM started working on a prototype system loosely based on Codd's
concepts as IBM System R|System R in the early 1970s
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Database management system - Late-1970s SQL DBMS
1 Stonebraker went on to apply the lessons from INGRES to develop a new database, Postgres, which is
now known as PostgreSQL. PostgreSQL is often used for global
mission critical applications (the .org and .info domain name registries use it as their primary data store, as do many large companies and financial
institutions).https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Database management system - Late-1970s SQL DBMS
1 In Sweden, Codd's paper was also read and Mimer SQL was developed
from the mid-1970s at Uppsala University. In 1984, this project was
consolidated into an independent enterprise. In the early 1980s, Mimer introduced transaction handling for high robustness in applications, an
idea that was subsequently implemented on most other DBMS.
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Databases - 1970s relational DBMS
1 In 1970, the University of Michigan began development of the MICRO Information
Management SystemWilliam Hershey and Carol Easthope,
[https://docs.google.com/open?id=0B4t_NX-QeWDYNmVhYjAwMWMtYzc3ZS00YjI0LWJhMjgtZTYyODZmNmFkNThh A set theoretic data structure and retrieval language], Spring Joint
Computer Conference, May 1972 in ACM SIGIR Forum, Volume 7, Issue 4 (December
1972), pp
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Object-relational database - Comparison to RDBMS
1 An RDBMS might commonly involve SQL
statements such as these:
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Object-relational database - Comparison to RDBMS
1 Id CHAR(12) NOT NULL PRIMARY KEY,
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Object-relational database - Comparison to RDBMS
1 FirstName VARCHAR(32) NOT
NULL,
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Object-relational database - Comparison to RDBMS
1 Most SQL databases allow the crafting of custom function
(computer science)|functions, which would allow the query to appear as:
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Object-relational database - Comparison to RDBMS
1 In an object-relational database, one might see something like this, with
user-defined data-types and expressions such as BirthDay():
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Object-relational database - Comparison to RDBMS
1 Id Cust_Id NOT NULL PRIMARY KEY,
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Object-relational database - Comparison to RDBMS
1 The object-relational model can offer another advantage in that the database can make use of the
relationships between data to easily collect related records. In an address book application, an additional table would be added to the ones above to hold zero or more addresses for each customer. Using a traditional RDBMS,
collecting information for both the user and their address requires a
join:
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Object-relational database - Comparison to RDBMS
1 FROM Customers C join Addresses A ON A.Cust_Id=C.Id
-- the join
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Object-relational database - Comparison to RDBMS
1 The same query in an object-relational database appears
more simply:
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Object-relational database - Comparison to RDBMS
1 WHERE C.address.city=New York -- the linkage is 'understood' by the ORDB
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RDBMS
1 A 'relational database management system' ('RDBMS') is a database
management system (DBMS) that is based on the relational model as introduced by Edgar F. Codd|E. F.
Codd, of IBM's IBM Almaden Research Center|San Jose Research Laboratory. Many popular databases
currently in use are based on the relational database model.
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RDBMS
1 RDBMSs have become since the 1980s a predominant choice for the
storage of information in new databases used for financial records,
manufacturing and logistical information, personnel data, and
much more
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RDBMS - Historical usage of the term
1 The term relational database was invented
by E
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RDBMS - Historical usage of the term
1 * Present the data to the user as relation (database)|relations (a
presentation in tabular form, i.e. as a collection of table (database)|tables with each table consisting of a set of
rows and columns);
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RDBMS - Historical usage of the term
1 * Provide relational operators to manipulate the data in
tabular form.
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RDBMS - Historical usage of the term
1 The first system sold as an RDBMS was Multics Relational Data Store, first sold in
1978
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RDBMS - Historical usage of the term
1 The most popular definition of an RDBMS is a product that presents a view of data as a collection of rows and columns, even if it is not based
strictly upon Relational model|relational theory. By this definition,
RDBMS products typically implement some but not all of Codd's 12 rules.
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RDBMS - Historical usage of the term
1 For clarification, they often refer to some RDBMSs as Truly-Relational Database Management Systems
(TRDBMS), naming others Pseudo-Relational Database Management
Systems (PRDBMS).
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RDBMS - Historical usage of the term
1 As of 2009, most commercial relational DBMSes employ SQL as their query language. Alternative
query languages have been proposed and implemented, notably the pre-1996 implementation of Berkeley
Ingres QUEL.
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Virtuoso Universal Server - Kubl RDBMS
1 The Kubl Object-relational database|ORDBMS was one of a list of
Relational database management system|relational database systems with roots in Finland. This list also
includes MySQL, InnoDB, and solidDB|Solid RDBMS/Solid
Technologies.
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Virtuoso Universal Server - Kubl RDBMS
1 As is the case with most technology products, key personnel behind
OpenLink Virtuoso, InnoDB, and Solid Technologies|Solid share periods of professional overlap that provide
noteworthy insight into the history of database technology development in
Finland
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Virtuoso Universal Server - Kubl RDBMS
1 Later, Orri Erling worked with VIA International, the developer of
VIA/DRE in designing a Lisp (programming language)|LISP based Object-oriented programming|object-oriented data access layer atop the company's Database management
system|DBMS product. The core development team of VIA, following the company's demise in 1992, went on to found Solid Technologies under
the direction of Artturi Tarjanne.
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Virtuoso Universal Server - Kubl RDBMS
1 Heikki Tuuri worked at Solid Technologies|Solid for a while before
starting his own database development project which became
InnoDB (acquired by Oracle Corporation|Oracle in 2005).
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Virtuoso Universal Server - Kubl RDBMS
1 Orri Erling started his own DBMS development work in 1994, which was to become Kubl
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Virtuoso Universal Server - Kubl RDBMS
1 A free trial version of Kubl was made available for download on November 7, 1996.
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Virtuoso Universal Server - Kubl RDBMS
1 Kubl was marketed as a high performance lightweight database for embedded software|embedded use; the development aim was to achieve top scores in Transactions
Per Second tests.[ http://sal.linet.gr.jp/H/1/KUBL.html]
Pricing of the product was especially favorable to Linux users with a Linux
license priced at $199.https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Virtuoso Universal Server - Kubl RDBMS
1 Kubl became the cornerstone of OpenLink Virtuoso, after the
technology paths of Kingsley Uyi Idehen and Orri Erling crossed in
1998, leading to the acquisition of Kubl by OpenLink Software.
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Persistence (computer science) - Database management systems (DBMSs)
1 DBMSs use a combination of the dirty writes and transaction journaling
techniques mentioned above. They provide not only persistence but also
other services such as queries, auditing and access control.
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Distributed database management system - Homogeneous DDBMS
1 *The Operating System used, at each location must be same
or compatible.
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Distributed database management system - Homogeneous DDBMS
1 *The data structures used at each
location must be same or compatible.
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Distributed database management system - Homogeneous DDBMS
1 *The database application (or DBMS) used at each location must be same or compatible.
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Distributed database management system - Heterogeneous DDBMS
1 On heterogeneous system, translations are required to allow communication between different
sites (or DBMS)
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Array DBMS
1 Array database management systems (DBMSs) provide Database
management system|database services specifically for array data structure|arrays (also called Raster
graphics|raster data), that is: homogeneous collections of data items (often called pixels, voxels,
etc.), sitting on a regular grid of one, two, or more dimensions.
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Array DBMS
1 Often arrays are used to represent sensor, simulation, image, or statistics data.
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Array DBMS
1 Such arrays tend to be Big data|Big Data, with single objects frequently
ranging into Terabyte and soon Petabyte sizes; for example, today’s
earth and space observation archives typically grow by Terabytes a day.
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Array DBMS - Overview
1 In the same style as standard Database Management System|
database systems do on sets, Array DBMSs offer scalable, flexible storage and flexible retrieval/manipulation on
arrays of (conceptually) unlimited size.
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Array DBMS - Overview
1 As in practice arrays never appear standalone, such an array model normally is embedded into some overall data model, such as the
relational model.
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Array DBMS - Overview
1 Some systems implement arrays as an analogy to tables, some introduce
arrays as an additional attribute type.
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Array DBMS - Overview
1 Management of arrays requires novel techniques, particularly due to the
fact that traditional database tuples and objects tend to fit well into a
single database page - a unit of disk access on server, typically 4 kB -
while array objects easily can span several media.
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Array DBMS - Overview
1 The prime task of the array storage manager is to give fast access to large arrays and sub-
arrays.
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Array DBMS - Overview
1 To this end, arrays get partitioned, during insertion, into so-called tiles or chunks of convenient size which then act as units of access during
query evaluation.
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Array DBMS - Overview
1 Array DBMSs offer Data Manipulation Language|query languages giving
Declarative programming|declarative access to such arrays, allowing to create, manipulate, search, and
delete them.
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Array DBMS - Overview
1 Like with, e.g., SQL, expressions of arbitrary complexity can be built on top of a set of core array operations.
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Array DBMS - Overview
1 Due to the extensions made in the data and query model, Array DBMSs sometimes are subsumed under the NoSQL category, in the sense of not
only SQL.
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Array DBMS - Overview
1 Query Query optimization|optimization and Parallel computing|
parallelization are important for achieving scalability; actually, many array operators lend themselves well
towards parallel evaluation, by processing each tile on separate
nodes or cores.
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Array DBMS - Overview
1 Important application domains of Array DBMSs include Earth, Space, Life, and Social sciences, as well as the related commercial applications (such as Oil exploration|hydrocarbon exploration in industry and OLAP in
business).
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Array DBMS - Overview
1 The variety occurring can be observed, e.g., in geo data where 1-D environmental sensor time series, 2-D satellite images, 3-D x/y/t image time series and x/y/z geophysics
data, as well as 4-D x/y/z/t climate and ocean data can be found.
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Array DBMS - History and Status
1 The Relational database|relational data model, which is prevailing
today, does not directly support the array paradigm to the same extent
as sets and tuples. International Organization for Standards|ISO SQL lists an array-valued attribute type,
but this is only one-dimensional, with almost no operational support, and
not usable for the #Application_Domains|application
domains of Array DBMSs.
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Array DBMS - History and Status
1 Another option is to resort to Binary large object|BLOBs (binary large
objects) which are the equivalent to files: byte strings of (conceptually) unlimited length, but again without any query language functionality,
such as multi-dimensional subsetting.
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Array DBMS - History and Status
1 First significant work in going beyond BLOBs has been established with PICDMS.Chock, M., Cardenas, A.,
Klinger, A.: Database structure and manipulation capabilities of a picture
database management system (PICDMS). IEEE ToPAMI, 6(4):484-492,
1984 This system offers the precursor of a 2-D array query
language, albeit still procedural and without suitable storage support.
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Array DBMS - History and Status
1 A first declarative query language suitable for multiple dimensions and with an algebra-based semantics has
been published by Peter Baumann (computer scientist)|Baumann,
together with a scalable architecture.Baumann, P.: [
http://www.informatik.uni-trier.de/~ley/db/journals/vldb/vldb3.html#Baum
ann94 On the Management of Multidimensional Discrete Data]
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Array DBMS - History and Status
1 Another array database language, constrained to 2-D, has been
presented by Marathe and Salem.Marathe, A., Salem, K.: A
language for manipulating arrays. Proc. VLDB’97, Athens, Greece,
August 1997, pages 46 - 55
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Array DBMS - History and Status
1 Seminal theoretical work has been accomplished by Libkin et al.;Libkin,
L., Machlin, R., Wong, L.: A query language for multidimensional
arrays: design, implementation and optimization techniques. Proc. ACM SIGMOD’96, Montreal, Canada, pp.
228 - 239 in their model, called NCRA, they extend a nested
relational calculus with multidimensional arrays; among the results are important contributions on array query complexity analysis.
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Array DBMS - History and Status
1 A map algebra, suitable for 2-D and 3-D spatial raster data, has been
published by Mennis et al.Mennis, J., Viger, R., Tomlin, C.D.: Cubic Map
Algebra Functions for Spatio-Temporal Analysis. Cartography and
Geographic Information Science 32(1)2005, pp. 17 - 32
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Array DBMS - History and Status
1 In terms of Array DBMS implementations, the rasdaman
system has the longest implementation track record of n-D
arrays with full query support.
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Array DBMS - History and Status
1 Oracle Spatial|Oracle GeoRaster offers chunked storage of 2-D raster maps, albeit without SQL integration.
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Array DBMS - History and Status
1 TerraLib is an open-source GIS software that extends object-
relational DBMS technology to handle spatio-temporal data types; while
main focus is on vector data, there is also some support for rasters.
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Array DBMS - History and Status
1 Starting with version 2.0, Postgis|PostGIS embeds raster support for 2-
D rasters; a special function offers declarative raster query functionality.
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Array DBMS - History and Status
1 SciQL is an array query language being added to the MonetDB DBMS. Michael_Stonebraker#SciDB|SciDB is a more recent initiative to establish array database support. Like SciQL, arrays are seen as an equivalent to tables, rather than a new attribute type as in rasdaman and PostGIS.
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Array DBMS - History and Status
1 For the special case of Sparse matrix|sparse data, OLAP data cubes are well established; they store cell
values together with their location - an adequate compression technique in face of the few locations carrying valid information at all - and operate
with SQL on them.
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Array DBMS - History and Status
1 As this technique does not scale in density, standard databases are not
used today for dense data, like satellite images, where most cells
carry meaningful information; rather, proprietary ad-hoc implementations
prevail in scientific data management and similar situations. Hence, this is where Array DBMSs
can make a particular contribution.https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Array DBMS - History and Status
1 Generally, Array DBMSs are an
emerging technology
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Array DBMS - Concepts
1 When adding arrays to databases, all facets of database design need to be
reconsidered - ranging from conceptual modeling (such as
suitable operators) over storage management (such as management
of arrays spanning multiple media) to query processing (such as efficient
processing strategies).
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Array DBMS - Conceptual Modeling
1 Formally, an array A is given by a (total or partial) function A: X → V where X, the domain
is a d-dimensional integer interval for some dsource lang=sql/sourcesource
lang=sql/sourcesource lang=sql/sourcesource lang=sql/sourcesource lang=sql/sourcesource lang=sql/sourcesource lang=sql/sourcesource lang=sql/sourcesource lang=sql/sourcesource
lang=sql/source foreseen is the [Open_Geospatial_Consortium |Open Geospatial
Consortium] (OGC) Coverage data|coverage model.
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Array DBMS - Standardization
1 Many communities have established data exchange formats, such as Hierarchical Data Format|HDF,
Netcdf|NetCDF, and Tagged Image File Format|TIFF.
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Array DBMS - Standardization
1 A de facto standard in the Earth Science communities is Opendap|
OPeNDAP, a data transport architecture and protocol. While this
is not a database specification, it offers important components that characterize a database system, such as a conceptual model and client/server implementations.
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Array DBMS - Standardization
1 A declarative geo raster query language, Web Coverage Processing
Service (WCPS), has been standardized by the Open Geospatial
Consortium (OGC).
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Database - General-purpose and special-purpose DBMSs
1 Database designers and database administrators interact with the
DBMS through dedicated interfaces to build and maintain the
applications' databases, and thus need some more knowledge and understanding about how DBMSs operate and the DBMSs' external interfaces and tuning parameters.
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Database - General-purpose and special-purpose DBMSs
1 General-purpose databases are usually developed by one
organization or community of programmers, while a different group builds the applications that use it. In
many companies, specialized database administrators maintain databases, run reports, and may
work on code that runs on the databases themselves (rather than in
the client application).https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Database - 1960s, navigational DBMS
1 The Codasyl approach was based on the manual navigation of a linked data set which was formed into a
large network
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Database - 1970s, relational DBMS
1 Edgar Codd worked at IBM in San Jose, California, in one of their
offshoot offices that was primarily involved in the development of hard
disk systems
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Database - 1970s, relational DBMS
1 Data may be freely inserted, deleted and edited in these tables, with the DBMS doing whatever maintenance
needed to present a table view to the application/user.
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Database - 1970s, relational DBMS
1 IBM itself did one test implementation of the relational
model, PRTV, and a production one, Business System 12, both now discontinued. Honeywell wrote
Multics Relational Data Store|MRDS for Multics, and now there are two new implementations: Dataphor|
Alphora Dataphor and Rel (DBMS)|Rel. Most other DBMS
implementations usually called relational are actually SQL DBMSs.
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Database - Late 1970s, SQL DBMS
1 IBM started working on a prototype system loosely based on Codd's
concepts as System R in the early 1970s
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Oracle RDBMS
1 The 'Oracle Database' (commonly referred to as 'Oracle RDBMS' or simply as 'Oracle') is an object-
relational database management system produced and marketed by
Oracle Corporation.
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Oracle RDBMS
1 Larry Ellison and his friends, former co-workers Bob Miner and Ed Oates,
started the consultancy Software Development Laboratories (SDL) in 1977. SDL developed the original
version of the Oracle software. The name Oracle comes from the code-
name of a Central Intelligence Agency|CIA-funded project Ellison had worked on while previously
employed by Ampex.https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Oracle RDBMS - Partitioning
1 Newer versions of the database can also include a Partition (database)|partitioning feature: this allows the
partitioning of tables based on different set of keys. Specific
partitions can then be easily added or dropped to help manage large
data sets.
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Oracle RDBMS - Corporate/technical timeline
1 * 1977: Larry Ellison and friends founded Software Development Laboratories (SDL).
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Oracle RDBMS - Corporate/technical timeline
1 * 1978: Oracle Version 1, written in assembly language, runs on PDP-11
under RSX, in 128K of memory. Implementation separates Oracle code and user code. Oracle V1 is
never officially released. http://www.oracle.com/us/corporate/p
rofit/p27anniv-timeline-151918.pdf
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Oracle RDBMS - Corporate/technical timeline
1 (RSI) and introduced its product Oracle V2 as an early relational
database system - often cited as the first commercially sold RDBMS
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Oracle RDBMS - Corporate/technical timeline
1 * 1982: RSI in its turn changed its name, becoming known as Oracle
Corporation,[ http://www.oracle.com/oramag/profit/
07-may/p27anniv_timeline.pdf Oracle.com] to align itself more closely with its flagship product.
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Oracle RDBMS - Corporate/technical timeline
1 * 1983: The company released Oracle version 3, which it had re-written using the C (programming
language)|C programming language and which supported Commit (data management)|COMMIT and Rollback
(data management)|ROLLBACK functionality for transactions. Version
3 extended platform support from the existing Digital Equipment
Corporation|Digital VAX/VMS systems to include Unix environments.
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Oracle RDBMS - Corporate/technical timeline
1 * 1984: Oracle Corporation released Oracle version 4, which supported
consistency model|read-consistency. In October it also released the first
Oracle for the IBM PC.
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Oracle RDBMS - Corporate/technical timeline
1 * 1985: Oracle Corporation released Oracle version 5, which supported the client–server model—a sign of networks becoming more widely
available in the mid-1980s.
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Oracle RDBMS - Corporate/technical timeline
1 * 1986: Oracle version 5.1 started supporting distributed computing|distributed queries.
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Oracle RDBMS - Corporate/technical timeline
1 * 1988: Oracle RDBMS version 6 came out with support for PL/SQL embedded within Oracle Forms v3
(version 6 could not store PL/SQL in the database proper), row-level lock (computer science)|locking and hot
backups.Compare [ http://www.oracle.com/oramag/profit/
07-may/p27anniv_timeline.pdf Oracle.com]
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Oracle RDBMS - Corporate/technical timeline
1 * 1989: Oracle Corporation entered the application software|application-products market and developed its Enterprise resource planning|ERP
product, (later to become part of the Oracle E-Business Suite), based on
the Oracle relational database.
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Oracle RDBMS - Corporate/technical timeline
1 * 1992: Oracle version 7 appeared with support for referential integrity,
stored procedures and database trigger|triggers.
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Oracle RDBMS - Corporate/technical timeline
1 * 1997: Oracle Corporation released version 8, which supported Object-
oriented programming|object-oriented development and multimedia applications.
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Oracle RDBMS - Corporate/technical timeline
1 * 1999: The release of Oracle8i aimed to provide a database inter-operating better with the Internet
(the i in the name stands for Internet). The Oracle8i database incorporated a native Java Virtual
Machine|Java virtual machine (Oracle JVM, also known as Aurora).
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Oracle RDBMS - Corporate/technical timeline
1 * 2000: Oracle E-Business Suite 11i pioneers integrated enterprise application software
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Oracle RDBMS - Corporate/technical timeline
1 * 2001: Oracle9i went into release with 400 new features, including the
ability to read and write XML documents. 9i also provided an option for Oracle RAC, or Real
Application Clusters, a computer cluster|computer-cluster database,
as a replacement for the Oracle Parallel Server (OPS) option.
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Oracle RDBMS - Corporate/technical timeline
1 * 2003: Oracle Corporation released Oracle Database 10g, which
supported regular expressions. (The g stands for grid; emphasizing a
marketing thrust of presenting 10g as grid computing ready.)
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Oracle RDBMS - Corporate/technical timeline
1 * 2006: Oracle Corporation announces Unbreakable Linux and
acquires i-flex
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Oracle RDBMS - Corporate/technical timeline
1 * 2007: Oracle Database 10g release 2 sets a new World Record TPC-H 3000 GB benchmark (computing)|
benchmark result
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Oracle RDBMS - Corporate/technical timeline
1 * 2007: Oracle Corporation released Oracle Database 11g for Linux and for Microsoft
Windows.
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Oracle RDBMS - Corporate/technical timeline
1 * 2008: Oracle Corporation acquires
BEA Systems.
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Oracle RDBMS - Corporate/technical timeline
1 * 2010: Oracle Corporation acquires Sun Microsystems.
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Oracle RDBMS - Corporate/technical timeline
1 * 2011: Oracle Corporation acquires web content management system FatWire
Software.
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Oracle RDBMS - Corporate/technical timeline
1 * 2011: On October 18, Oracle Corporation acquires Endeca
Technologies Inc. faceted search engine software vendor.
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Oracle RDBMS - Corporate/technical timeline
1 for Linux, Solaris (Operating System)|Solaris and Microsoft
Windows|Windows. (The c stands for cloud.)
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Oracle RDBMS - Version numbering
1 With the Oracle RDBMS 10g release, Oracle Corporation began using the 10g label in all versions of its major products, although some sources
refer to Oracle Applications Release 11i as Oracle 11i
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Oracle RDBMS - Version numbering
1 Major database-related products and some of their versions include:
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Oracle RDBMS - Version numbering
1 * Oracle Application Server 10g (also known as Oracle AS 10g): a
Middleware (distributed applications)|middleware product;
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Oracle RDBMS - Version numbering
1 * Oracle Applications Release 11i (aka Oracle e-Business Suite, Oracle Financials or Oracle 11i): a software suite|suite of business applications;
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Oracle RDBMS - Version numbering
1 * Oracle Developer Suite 10g (9.0.4);
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Oracle RDBMS - Version numbering
1 * JDeveloper|Oracle JDeveloper 10g: a Java (programming language)|Java
integrated development environment;
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Oracle RDBMS - Version numbering
1 Since version 2, Oracle's Relational database management system|
RDBMS release numbering has used the following codes:
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Oracle RDBMS - Version numbering
1 * Oracle9i Database Release 1: 9.0.1.0–
9.0.1.5 (patch (computing)|
Patchset )https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Oracle RDBMS - Version numbering
1 The version-numbering syntax within each release follows the pattern: major.maintenance.application-
server.component-specific.platform-specific.
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Oracle RDBMS - Version numbering
1 The [ http://docs.oracle.com/cd/B14117_01/server.101/b10739/dba.htm#sthref3
5 Oracle Database Administrator's Guide] offers further information on
Oracle release numbers.
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Oracle RDBMS - Host platforms
1 Prior to releasing Oracle 9i in 2001, Oracle Corporation ported its
database product to a wide variety of platforms. Subsequently Oracle Corporation consolidated on a
smaller range of operating-system platforms.
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Oracle RDBMS - Host platforms
1 , Oracle Corporation supported the following Operating Systems and
hardware platforms for Oracle Database 11g (11.2.0.2.0):[
http://www.oracle.com/pls/db112/portal.portal_db?selected=11 Oracle
Database Online Documentation 11g Release 2 (11.2)]
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Oracle RDBMS - Host platforms
1 In 2011, Oracle Corporation announced the availability of Oracle Database Appliance, a pre-built, pre-
tuned, highly available clustered database server built using two SunFire X86 servers and direct
attached storage.
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Oracle RDBMS - Host platforms
1 Some Oracle Enterprise edition databases running on certain Oracle-supplied hardware
can utilize
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Oracle RDBMS - Host platforms
1 Hybrid Columnar Compression for more efficient
storage.
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Rel (DBMS)
1 'Rel' is an open source true relational model|relational database management system that
implements a significant portion of Christopher J. Date|Chris Date and Hugh Darwen's D (data language
specification)|Tutorial D query language.
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Rel (DBMS)
1 Primarily intended for teaching purposes, Rel is written in the Java
(programming language)|Java programming language.
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General-purpose DBMS
1 A 'database' is an organized collection of Data (computing)|data. The data are typically organized to
model relevant aspects of reality in a way that supports processes requiring this information. For
example, modeling the availability of rooms in hotels in a way that supports finding a hotel with
vacancies.https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
General-purpose DBMS
1 A database is not generally Software portability|portable across different
DBMSs, but different DBMSs can interoperate by using Technical
standard|standards such as SQL and ODBC or JDBC to allow a single
application to work with more than one database.
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General-purpose DBMS - 1980s, object-oriented
1 This allows for relations between data to be relations to objects and
their attributes and not to individual fields.Development of an object-oriented DBMS; Portland, Oregon, United States; Pages: 472 – 482;
1986; ISBN 0-89791-204-7 The term object-relational impedance
mismatch described the inconvenience of translating between
programmed objects and database tables
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General-purpose DBMS - Research
1 Database technology has been an active research topic since the
1960s, both in academia and in the research and development groups of
companies (for example IBM Research). Research activity includes
Database theory|theory and development of prototypes. Notable research topics have included Data
model|models, the atomic transaction concept and related concurrency control techniques,
query languages and query optimization methods, RAID, and
more.
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General-purpose DBMS - Research
1 The database research area has several dedicated academic journals (for example, ACM Transactions on Database Systems-TODS, Data and Knowledge Engineering-DKE) and
annual Academic conference|conferences (e.g., Association for
Computing Machinery|ACM SIGMOD, ACM Symposium on Principles of
Database Systems|PODS, VLDB, IEEE ICDE).https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
General-purpose DBMS - Models
1 A database model is a type of data model that determines the logical
structure of a database and fundamentally determines in which
manner data can be stored, organized, and manipulated. The
most popular example of a database model is the relational model (or the
SQL approximation of relational), which uses a table-based format.
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General-purpose DBMS - Models
1 Common logical data models for
databases include:
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General-purpose DBMS - Models
1 * Entity–attribute–value model
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General-purpose DBMS - Models
1 An object-relational database combines the two related
structures.
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General-purpose DBMS - Models
1 Physical data models include:
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General-purpose DBMS - Models
1 * Multidimensional database|
Multidimensional model
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General-purpose DBMS - Models
1 * Multivalue model
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General-purpose DBMS - Materialized views
1 Often storage redundancy is employed to increase performance. A common example is storing materialized views, which consist of frequently needed external views or query
results. Storing such views saves the expensive computing of them each time they are needed. The downsides of materialized
views are the overhead incurred when updating them to keep them synchronized with their original updated database data,
and the cost of storage redundancy.
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General-purpose DBMS - Replication
1 Occasionally a database employs storage redundancy by database objects replication (with one or more copies) to increase data
availability (both to improve performance of simultaneous multiple end-user accesses to a
same database object, and to provide resiliency in a case of partial failure of a
distributed database). Updates of a replicated object need to be synchronized across the
object copies. In many cases the entire database is replicated.
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General-purpose DBMS - Migration
1 Typically a DBMS vendor provides tools to help importing databases from other popular
DBMSs.
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Strozzi NoSQL (RDBMS)
1 Its file name NoSQL merely reflects the fact that it does not express its
queries using Structured Query Language; the NoSQL RDBMS is
distinct from the circa-2009 general concept of NoSQL|NoSQL databases,
which are typically non-relational, unlike the NoSQL RDBMS
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Strozzi NoSQL (RDBMS) - Construction
1 NoSQL uses the operator-stream paradigm, where a number of
operators perform a unique function on the passed data. The stream used is supplied by the UNIX input/output redirection system so that over the
Pipeline (Unix)|pipe system, the result of the calculation can be
passed to other operators. As UNIX pipes run in memory, it is a very efficient way of implementation.
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Strozzi NoSQL (RDBMS) - Construction
1 NoSQL, with development led by Carlo Strozzi, is the latest and
perhaps the most active in a line of implementations of the stream-
operator database design originally described by Evan Shaffer, Rod
Manis, and Robert Jorgensen in a 1991 Unix Review article and an [ http://www.rdb.com/lib/4gl.pdf
associated paper]https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Strozzi NoSQL (RDBMS) - Construction
1 The concept was originally described in a 1991 Unix Review article, and
later expanded in a paper (see reference above), as well as in the
book, Unix Relational Database Management
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Strozzi NoSQL (RDBMS) - Construction
1 NoSQL is written mostly in interpretive languages, slowing actual process execution, but its ability to use ordinary pipes and filesystems means that it can be
extremely fast for many applications when using RAM filesystems or
heavily leveraging pipes, which are mostly memory-based in many
implementations.https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Strozzi NoSQL (RDBMS) - Philosophy
1 # Complexity: Most commercial database products are often too
costly for minor projects, and free databases are too complex. They also do not have the shell-level
approach that NoSQL has.
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Strozzi NoSQL (RDBMS) - Philosophy
1 ## Data: The data from NoSQL can be easily ported to other types of
machines, like Macintoshes or Windows computers, since tables
exist as simple ASCII text and can be easily read from or redirected to files
at any point in processing.
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Strozzi NoSQL (RDBMS) - Philosophy
1 ## Software: NoSQL can run on any UNIX machine that has the Perl and the AWK programming languages installed, and perhaps even on the Cygwin UNIX-like environment for
Microsoft Windows.
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Strozzi NoSQL (RDBMS) - Philosophy
1 # Unlimited: NoSQL has zero one infinity rule | no arbitrary limits, like a
data field size, column number, or file size limit, and can principally
work where other products cannot. (The number of columns in a table
may actually be limited to 32,768 by some implementations of the AWK1
programming language).
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Strozzi NoSQL (RDBMS) - Philosophy
1 # Usability: With its straight forward and logical concept, NoSQL can easily be used by non-computer
people. For instance, rows of data are selected with the 'row' operator,
columns with the 'column' operator.
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Strozzi NoSQL (RDBMS) - Philosophy
1 In contrast to other RDBMS, NoSQL has the full power of UNIX during
application development and usage
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PowerBuilder - RDBMS Interfaces
1 PowerBuilder offers native interfaces to all major databases, as well as ODBC and OLE DB|OLE-DB, in the
Enterprise version. There are many connectivity options that allow
performance monitoring and tuning, such as:
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PowerBuilder - RDBMS Interfaces
1 Due to the information about the database schema (such as primary key information) that are stored in PowerBuilder's data dictionary, the code required to implement data display and browsing is greatly
simplified, because the dictionary information allows generation of the appropriate SQL behind the scenes.
Here is a sample PowerBuilder update script:
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PowerBuilder - RDBMS Interfaces
1 PowerBuilder supports the following ways of
interacting with a database:
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PowerBuilder - RDBMS Interfaces
1 DataWindow: this is the simplest approach, relying on automatically generated SQL.
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PowerBuilder - RDBMS Interfaces
1 ;Embedded SQL: Embedded SQL supports SELECT, INSERT, UPDATE, DELETE and cursors. This option is used when the developer desires
more control than is available with the DataWindow option. Example:
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PowerBuilder - RDBMS Interfaces
1 ;Dynamic SQL: This is a form of parameterized SQL, where the user builds a string that may optionally have bind variables. Dynamic SQL may be used to create cursors as
well.
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Correlation database - Storage in RDBMS
1 The record-based structure used in an RDBMS stores data in with
elements of the row most near each other. Variations like Index
(database)|clustered indexing may change the sequence of the rows,
but all rows, columns and values will be stored as in the table. The above
table might be stored as:
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Correlation database - Storage in RDBMS
1 12222,ABC Corp,Minneapolis,MN;19434,A1
Mfg,Duluth,MN;20523,JJ Inc,St. Paul,MN
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Correlation database - Storage in CDBMS
1 In the VBS structure used in a CDBMS, each unique value is stored
once and given an abstract (numeric) identifier, regardless of the number of occurrences or locations in the
original data set. The original dataset is then constructed by referencing
those logical identifiers. The correlation index may resemble the storage below. Note that the value MN which occurs multiple times in
the data above is only included once. As the amount of repeat data grows,
this benefit multiplies.
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Correlation database - Storage in CDBMS
1 1:12222,2:19434,3:20523,4:ABC Corp,5:A1 Mfg,6:JJ
Inc,7:Minneapolis,8:Duluth,9:St.Paul,10:MN
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Correlation database - Storage in CDBMS
1 The records in our example table
above can then be expressed as:
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Correlation database - Storage in CDBMS
1 However, in a traditional RDBMS this normalization process requires work in the form of table configuration,
stored procedures, and SQL statements
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Correlation database - Storage in CDBMS
1 This correlation process is similar to what occurs in a text-search oriented Inverted
index.
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Database management systems - 1970s, relational DBMS
1 In 1970, the University of Michigan began development of the MICRO Information
Management SystemWilliam Hershey and Carol Easthope,
[https://docs.google.com/open?id=0B4t_NX-QeWDYNmVhYjAwMWMtYzc3ZS00YjI0LWJhMjgtZTYyODZmNmFkNThh A set theoretic data structure and retrieval language], Spring Joint
Computer Conference, May 1972 in ACM SIGIR Forum, Volume 7, Issue 4 (December
1972), pp
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Database tuning - DBMS tuning
1 DBMS tuning refers to tuning of the DBMS and the configuration of the
memory and processing resources of the computer running the DBMS. This is typically done through configuring the DBMS, but the resources involved
are shared with the host system.
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Database tuning - DBMS tuning
1 Tuning the DBMS can involve setting the recovery interval (time needed to
restore the state of data to a particular point in time), assigning Parallel computing|parallelism (the breaking up of work from a single
query into tasks assigned to different processing resources), and
Communications protocol|network protocols used to communicate with
database consumers.https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Database tuning - DBMS tuning
1 Memory is allocated for data, Query plan|execution plans, procedure cache, and
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Database tuning - DBMS tuning
1 Processing resources are sometimes assigned to specific activities to improve Concurrency (computer
science)|concurrency. On a Server (computing)|server with eight
processors, six could be reserved for the DBMS to maximize available
processing resources for the database.
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DBMS - Terminology and overview
1 Formally, database refers to the data themselves and supporting data structures.
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DBMS - Terminology and overview
1 Databases are created to operate large quantities of information by inputting, storing, retrieving, and
managing that information. Databases are set up so that one set
of software programs provides all users with access to all the data.
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DBMS - Terminology and overview
1 A database management system (DBMS) is a suite of computer
software providing the interface between users and a database or databases. Because they are so
closely related, the term database when used casually often refers to
both a DBMS and the data it manipulates.
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DBMS - Terminology and overview
1 Outside the world of professional information technology, the term
database is sometimes used casually to refer to any collection of data
(perhaps a spreadsheet, maybe even a card index). This article is
concerned only with databases where the size and usage
requirements necessitate use of a database management
system.Jeffrey Ullman 1997: First course in database systems,
Prentice–Hall Inc., Simon Schuster, Page 1, ISBN 0-13-861337-0.
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DBMS - Terminology and overview
1 The interactions catered for by most existing DBMSs fall into four main groups:
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DBMS - Terminology and overview
1 * 'Data definition' – Defining new data structures for a database,
removing data structures from the database, modifying the structure of
existing data.
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DBMS - Terminology and overview
1 * 'Update' – Inserting, modifying, and deleting
data.
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DBMS - Terminology and overview
1 * 'Retrieval' – Obtaining information either for end-user queries and
reports or for processing by applications.
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DBMS - Terminology and overview
1 * 'Administration' – Registering and monitoring users, enforcing data
security, monitoring performance, maintaining data integrity, dealing
with concurrency control, and recovering information if the system
fails.
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DBMS - Terminology and overview
1 A DBMS is responsible for maintaining the integrity and
security of stored data, and for recovering information if the system
fails.
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DBMS - Terminology and overview
1 Both a database and its DBMS conform to the principles of a particular database
model.Tsitchizris, D. C. and F. H. Lochovsky (1982). Data Models.
Englewood-Cliffs, Prentice–Hall. Database system refers collectively to the database
model, database management system, and database.Beynon-Davies P. (2004).
Database Systems 3rd Edition. Palgrave, Basingstoke, UK. ISBN 1-4039-1601-2
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DBMS - Terminology and overview
1 Since DBMSs comprise a significant Economy|economical market,
computer and storage vendors often take into account DBMS
requirements in their own development plans.
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DBMS - Terminology and overview
1 Databases and DBMSs can be categorized according to the
database model(s) that they support (such as relational or XML), the type(s) of computer they run on
(from a server cluster to a mobile phone), the query language(s) used to access the database (such as SQL
or XQuery), and their internal engineering, which affects
performance, scalability, resilience, and security.
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DBMS - History
1 With the data progress in technology in the areas of processors, computer
memory, computer storage and computer networks, the sizes,
capabilities, and performance of databases and their respective DBMSs have grown in orders of
magnitudes.
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DBMS - History
1 The development of database technology can be divided into three
eras based on data model or structure: navigational database|
navigational, (Turing Award Lecture 1973) SQL/relational database|
relational, and post-relational. The two main early navigational data
models were the Hierarchical database model|hierarchical model, epitomized by IBM's IMS system, and the Codasyl model (Network model),
implemented in a number of products such as IDMS.
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DBMS - History
1 It was not until the mid-1980s that computing hardware became
powerful enough to allow relational systems (DBMSs plus applications) to
be widely deployed
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DBMS - History
1 Object databases were invented in the 1980s to overcome the
inconvenience of object-relational impedance mismatch, which led to
the coining of the term post-relational but also development of hybrid object-relational databases.
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DBMS - History
1 The next generation of post-relational databases in the 2000s became known as
NoSQL databases, introducing fast key-value stores and document-oriented
databases. A competing next generation known as NewSQL databases attempted new implementations that retained the
relational/SQL model while aiming to match the high performance of NoSQL compared
to commercially available relational DBMSs.
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DBMS - 1970s, relational DBMS
1 In 1970, the University of Michigan began development of the MICRO
Information Management SystemWilliam Hershey and Carol
Easthope, [https://docs.google.com/open?
id=0B4t_NX-QeWDYNmVhYjAwMWMtYzc3ZS00YjI0LWJhMjgtZTYyODZmNmFkNThh A
set theoretic data structure and retrieval language], Spring Joint
Computer Conference, May 1972 in ACM SIGIR Forum, Volume 7, Issue 4
(December 1972), pp
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DBMS - 1980s, on the desktop
1 The 1980s ushered in the age of Desktop Computer|desktop
computing
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DBMS - Examples
1 One way to classify databases involves the type of their contents,
for example: Bibliographic database|bibliographic, document-text,
statistical, or multimedia objects. Another way is by their application
area, for example: accounting, music compositions, movies, banking,
manufacturing, or insurance. A third way is by some technical aspect, such as the database structure or interface type. This section lists a
few of the adjectives used to characterize different kinds of
databases.
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DBMS - Examples
1 * An in-memory database is a database that primarily resides in
main memory, but is typically backed-up by non-volatile computer
data storage
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DBMS - Examples
1 * An active database includes an event-driven architecture which can
respond to conditions both inside and outside the database. Possible uses
include security monitoring, alerting, statistics gathering and
authorization. Many databases provide active database features in
the form of database triggers.
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DBMS - Examples
1 * A cloud database relies on Cloud computing|cloud technology. Both the database and most of its DBMS reside remotely, in the cloud, while its applications are both developed
by programmers and later maintained and utilized by
(application's) end-users through a web browser and Open APIs.
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DBMS - Examples
1 * Data warehouses archive data from operational databases and often from
external sources such as market research firms
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DBMS - Examples
1 * A deductive database combines logic programming with a relational database, for example by using the
Datalog language.
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DBMS - Examples
1 * A distributed database is one in which both the data and the DBMS span multiple
computers.
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DBMS - Examples
1 * A document-oriented database is designed for storing, retrieving, and
managing document-oriented, or semi structured data, information. Document-oriented databases are
one of the main categories of NoSQL databases.
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DBMS - Examples
1 * An embedded database system is a DBMS which is tightly integrated with an application software that requires access to stored data in such a way that the DBMS is hidden from the
application’s end-users and requires little or no ongoing maintenance.Graves, Steve. [
http://www.embedded-computing.com/articles/id/?2020 COTS Databases For Embedded Systems], Embedded Computing Design
magazine, January 2007. Retrieved on August 13, 2008.
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DBMS - Examples
1 *'End-user databases' consist of data developed by individual end-users. Examples of these are collections of
documents, spreadsheets, presentations, multimedia, and other
files. Several products exist to support such databases. Some of them are much simpler than full
fledged DBMSs, with more elementary DBMS functionality.
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DBMS - Examples
1 * A federated database system comprises several distinct databases, each with its own DBMS. It is handled as a single database by a federated
database management system (FDBMS), which transparently
integrates multiple autonomous DBMSs, possibly of different types (in
which case it would also be a heterogeneous database system),
and provides them with an integrated conceptual view.
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DBMS - Examples
1 * Sometimes the term multi-database is used as a synonym to federated database, though it may
refer to a less integrated (e.g., without an FDBMS and a managed
integrated schema) group of databases that cooperate in a single
application
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DBMS - Examples
1 * A graph database is a kind of NoSQL database that uses Graph (data structure)|graph structures
with nodes, edges, and properties to represent and store information.
General graph databases that can store any graph are distinct from
specialized graph databases such as triplestores and network database
model|network databases.https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
DBMS - Examples
1 * In a hypertext or hypermedia database, any word or a piece of text representing an object, e.g., another piece of text, an article, a picture, or
a film, can be hyperlinked to that object. Hypertext databases are particularly useful for organizing
large amounts of disparate information. For example, they are
useful for organizing online encyclopedias, where users can
conveniently jump around the text. The World Wide Web is thus a large
distributed hypertext database.
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DBMS - Examples
1 *A knowledge base (abbreviated 'KB', 'kb' or ΔArgumentation in Artificial
Intelligence by Iyad Rahwan, Guillermo R. Simari) is a special kind
of database for knowledge management, providing the means
for the computerized collection, organization, and Information
retrieval|retrieval of knowledge. Also a collection of data representing problems with their solutions and
related experiences.
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DBMS - Examples
1 * A mobile database can be carried on or synchronized from a mobile computing
device.
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DBMS - Examples
1 * Operational databases store detailed data about the operations of an organization
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DBMS - Examples
1 * A parallel database seeks to improve performance through
Parallel computing|parallelization for tasks such as loading data, building
indexes and evaluating queries.
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DBMS - Examples
1 ::The major parallel DBMS architectures which are induced by the underlying Computer hardware|
hardware architecture are:
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DBMS - Examples
1 ::* 'Shared memory#In hardware|Shared memory architecture', where multiple processors share the main
memory space, as well as other data storage.
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DBMS - Examples
1 ::* 'Shared disk architecture', where each processing unit (typically
consisting of multiple processors) has its own main memory, but all units
share the other storage.
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DBMS - Examples
1 ::* 'Shared nothing architecture', where each processing unit has its
own main memory and other storage.
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DBMS - Examples
1 * Probabilistic databases employ fuzzy logic to draw inferences from imprecise data.
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DBMS - Examples
1 * Real-time databases process transactions fast enough for the
result to come back and be acted on right away.
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DBMS - Examples
1 * A spatial database can store the data with multidimensional features.
The queries on such data include location based queries, like Where is
the closest hotel in my area?.
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DBMS - Examples
1 * A temporal database has built-in time aspects, for example a temporal data model and a temporal version of SQL. More specifically the temporal aspects usually include valid-time
and transaction-time.
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DBMS - Examples
1 * A terminology-oriented database builds upon an object-oriented
database, often customized for a specific field.
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DBMS - Examples
1 Most established DBMSs now support unstructured data in various ways,
and new dedicated DBMSs are emerging.
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DBMS - Languages
1 Database languages are special-purpose languages, which do one or more of the
following:
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DBMS - Languages
1 * Data definition language – defines data types and the relationships among them
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DBMS - Languages
1 * Data manipulation language – performs tasks such as inserting,
updating, or deleting data occurrences
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DBMS - Languages
1 * Query language – allows searching for information and computing derived
information
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DBMS - Languages
1 Database languages are specific to a particular data model. Notable examples
include:
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DBMS - Languages
1 The standards have been regularly enhanced since and is supported
(with varying degrees of conformance) by all mainstream
commercial relational DBMSs.
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DBMS - Languages
1 * OQL is an object model language standard (from the Object Data
Management Group). It has influenced the design of some of the newer query languages like JDOQL
and EJB QL.
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DBMS - Languages
1 * XQuery is a standard XML query language implemented by XML
database systems such as MarkLogic and eXist, by relational databases with XML capability such as Oracle
and DB2, and also by in-memory XML processors such as Saxon XSLT|
Saxon.
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DBMS - Languages
1 A database language may also
incorporate features like:
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DBMS - Languages
1 * DBMS-specific Configuration and
storage engine management
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DBMS - Languages
1 * Computations to modify query results, like counting, summing,
averaging, sorting, grouping, and cross-referencing
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DBMS - Languages
1 * Constraint enforcement (e.g. in an automotive database, only allowing one
engine type per car)
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DBMS - Languages
1 * Application programming interface version of the query language, for programmer
convenience
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DBMS - Other
1 Other DBMS features might
include:
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DBMS - Other
1 * Graphics component for producing graphs and charts, especially in a data warehouse
system
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DBMS - Other
1 *'Query optimizer' – Performs query optimization on every query to
choose for it the most efficient query plan (a partial order (tree) of operations) to be executed to
compute the query result. May be specific to a particular storage
engine.
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DBMS - Other
1 * Tools or hooks for database design, application programming, application
program maintenance, database performance analysis and monitoring,
database configuration monitoring, DBMS hardware configuration (a DBMS and related database may span computers, networks, and storage units) and related database
mapping (especially for a distributed DBMS), storage allocation and database layout
monitoring, storage migration, etc.
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Database Management - 1970s, relational DBMS
1 In 1970, the University of Michigan began development of the MICRO Information
Management SystemWilliam Hershey and Carol Easthope,
[https://docs.google.com/open?id=0B4t_NX-QeWDYNmVhYjAwMWMtYzc3ZS00YjI0LWJhMjgtZTYyODZmNmFkNThh A set theoretic data structure and retrieval language], Spring Joint
Computer Conference, May 1972 in ACM SIGIR Forum, Volume 7, Issue 4 (December
1972), pp
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ORDBMS
1 An 'object-relational database' ('ORD'), or 'object-relational database management system' ('ORDBMS'), is
a database management system (DBMS) similar to a relational
database, but with an object-oriented database model: objects, classes and inheritance are directly supported in database schemas and in the query language. In addition, just as with pure relational systems, it supports extension of the data model with custom data type|data-types and
method (computer science) |methods.
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ORDBMS
1 In object-relational databases, the approach is essentially that of relational databases: the
data resides in the database and is manipulated collectively with queries in a query language; at the other extreme are
OODBMSes in which the database is essentially a persistent object store for software written in an object-oriented
programming language, with a programming API for storing and retrieving objects, and little or no specific support for querying.
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ORDBMS - Overview
1 Whereas traditional RDBMS or SQL-DBMS products focused on the
efficient management of data drawn from a limited set of data-types
(defined by the relevant language standards), an object-relational
DBMS allows software developers to integrate their own types and the
methods that apply to them into the DBMS.
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ORDBMS - Overview
1 'Complex data' creation in most SQL ORDBMSs is based on preliminary
schema definition via the user-defined type (UDT)
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ORDBMS - Overview
1 In object-oriented programming|object-oriented programming (OOP), object behavior is described through
the methods (object functions)
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ORDBMS - History
1 Object-relational database management systems grew out of research that occurred in
the early 1990s
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ORDBMS - History
1 By the next decade, PostgreSQL had become a commercially viable
database, and is the basis for several current products that maintain its
ORDBMS features.
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ORDBMS - History
1 Computer scientists came to refer to these products as object-relational database management systems or ORDBMSs.There was, at the time, a
dispute whether the term was coined by Michael Stonebraker of Illustra or
Won Kim of UniSQL.
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ORDBMS - History
1 Many of the ideas of early object-relational database efforts have largely become incorporated into SQL|SQL:1999 via
structured types. In fact, any product that adheres to the object-oriented aspects of
SQL:1999 could be described as an object-relational database management product. For
example, IBM's IBM DB2|DB2, Oracle database, and Microsoft SQL Server, make claims to support this technology and do so
with varying degrees of success.
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List of GIS software - Spatial DBMS
1 * Spatial Query Server|Boeing's Spatial Query Server ndash; Spatially enables Sybase ASE.
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List of GIS software - Spatial DBMS
1 * IBM DB2|DB2 ndash; Allows spatial querying and storing of most spatial data types.
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List of GIS software - Spatial DBMS
1 * Informix ndash; Allows spatial querying and storing of most spatial data types.
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List of GIS software - Spatial DBMS
1 * MySQL ndash; Allows spatial querying and storing of most spatial data types.
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List of GIS software - Spatial DBMS
1 * Microsoft SQL Server (2008 and later) ndash; The latest player in the
market of storing and querying spatial data. GIS products such as MapInfo and Cadcorp SIS can read and edit this data while ESRI and others are expected to be able to read and edit this data within the
next few months.
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List of GIS software - Spatial DBMS
1 * Oracle Spatial ndash; Product allows users to perform complex geographic operations and store common spatial data types in a native Oracle environment. Most
commercial GIS packages can read and edit spatial data stored in this
way.
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List of GIS software - Spatial DBMS
1 * PostGIS ndash; A mature set of
extensions to the free PostgreSQL
database.https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
List of GIS software - Spatial DBMS
1 * Teradata Geospatial|Teradata ndash; Teradata geospatial allows
storage and spatial analysis on location-based data which is stored using native geospatial data-types
within the Teradata database.
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Micro DBMS
1 The 'MICRO Information Management System' was the first-large scale set-theoretic database management system to be used in
production.[https://docs.google.com/open?id=0B4t_NX-
QeWDYNmVhYjAwMWMtYzc3ZS00YjI0LWJhMjgtZTYyODZmNmFkNThh A
set theoretic data structure and retrieval language (PDF)], William R
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Micro DBMS
1 Implementation of MICRO began in 1970 as part of the Labor Market
Information System (LMIS) project at the University of Michigan's Institute
of Labor and Industrial Relations (ILIR)
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Micro DBMS
1 MICRO runs under the Michigan Terminal System (MTS), the
interactive time-sharing system developed at the University of
Michigan that runs on IBM System/360 Model 67, System/370,
and compatible mainframe computers.[http://babel.hathitrust.or
g/cgi/pt?view=image;size=100;id=mdp.3901
5014920717;page=root;seq=5 Chapter 6: MICRO in Introduction to database management systems on MTS], Rick Rilio, User Guide Series,
Computing Center, University of Michigan, March 1986, pages 147-
189 MICRO provides a query language, a database directory, and
a data dictionary to create an interface between the user and the
very efficient proprietary Set-Theoretic Data Structure (STDS) software developed by the Set-Theoretic Information Systems
Corporation (STIS) of Ann Arbor, Michigan
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Micro DBMS
1 MICRO permits users with little programming experience to define, enter, interrogate, manipulate, and
update collections of data in a relatively unstructured and unconstrained environment
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Data Base - 1960s, navigational DBMS
1 As computers grew in speed and capability, a number of general-
purpose database systems emerged; by the mid-1960s a number of such systems had come into commercial
use
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Data Base - 1960s, navigational DBMS
1 The CODASYL approach relied on the manual navigation of a linked data set which was formed into a large network. Applications could find
records by one of three methods:
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Data Base - 1960s, navigational DBMS
1 #Use of a primary key (known as a CALC key, typically implemented by hashing)
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Data Base - 1960s, navigational DBMS
1 #Scanning all the records in a sequential
order
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Data Base - 1960s, navigational DBMS
1 Later systems added B-Trees to provide alternate access paths. Many
CODASYL databases also added a very straightforward query language. However, in the final tally, CODASYL
was very complex and required significant training and effort to
produce useful applications.
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Data Base - 1960s, navigational DBMS
1 International Business Machines|IBM also had their own DBMS in 1968,
known as IBM Information Management System|Information
Management System (IMS)
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Data Base - 1970s, relational DBMS
1 Edgar F
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Data Base - 1970s, relational DBMS
1 In 1970, the University of Michigan began development of the MICRO Information
Management SystemWilliam Hershey and Carol Easthope,
[https://docs.google.com/open?id=0B4t_NX-QeWDYNmVhYjAwMWMtYzc3ZS00YjI0LWJhMjgtZTYyODZmNmFkNThh A set theoretic data structure and retrieval language], Spring Joint
Computer Conference, May 1972 in ACM SIGIR Forum, Volume 7, Issue 4 (December
1972), pp
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Data Base - Late 1970s, SQL DBMS
1 Another data model, the entity–relationship model, emerged in 1976 and gained popularity for database
design as it emphasized a more familiar description than the earlier relational model. Later on, entity–
relationship constructs were retrofitted as a data modeling
construct for the relational model, and the difference between the two
have become irrelevant.https://store.theartofservice.com/itil-2011-foundation-complete-certification-kit-fourth-edition-study-guide-ebook-and-online-course.html
Database management program - General-purpose and special-purpose DBMSs
1 how to find the required database in sufficient coding level of all clients in
such an aspirant data viewing objects .
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