The Death of the Databasemedia.govtech.net/GOVTECH_WEBSITE/EVENTS/PRESENTATION_DO… · SOA –...
Transcript of The Death of the Databasemedia.govtech.net/GOVTECH_WEBSITE/EVENTS/PRESENTATION_DO… · SOA –...
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Notes accompany this presentation. Please select Notes Page view. These materials can be reproduced only with Gartner's official approval. Such approvals may be requested via e-mail — [email protected].
The Death of the Database
Mark Beyer
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c. 1700 b.c., Mycenaean Linear B
c. 2700 b.c., Minoan Linear A
Database-Dependent SQL Will Be Taken Away and Context Will Be Real Time
Defining persistenceThink of verbs
– Storage– Access– Delivery– Utilization/usage
c. 2700 b.c.,Sumerian Literature
c. 300 b.c. "0" invented Babylon
c. 350 c.e., "0" invented Mayan
c. 458 c.e. "0" invented India
c. 1750 c.e., Industrial Revolution
1889 Hollerith's Statistical Census method
c. 1989 Internet Revolution
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Key Issues
1. How quickly will databases become obsolete?
2. Why do service-oriented architectures change data persistence beyond recognition?
3. Will any of your products and skills remain relevant?
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Key Issues
1. How quickly will databases become obsolete?
2. Why do service-oriented architectures change data persistence beyond recognition?
3. Will any of your products and skills remain relevant?
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MonolithicApp. DB
Storage Changes
Grid — the network becomes the database?QueuesProgrammatic persistence yields to a policy scenarioIndexing beyondthe databaseMicroscale persistenceat the asset
Services?Services?
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Storage Changes: Distribution of Persistence
Everything carries its own dataRFID examples– Grocery store inventory – OnStar– Rental cars
Months
Relative Performance
010203040506070
0 12 24 36 48 60 72 84 96 108
Moore's Law
Hours FTE
Technology Deployed
250
Manual EDW EDW/BI
Analytic innovation effect on SKU case study
0
50
100
150
200
Asset ID
Descriptors
Categorization ID
Amortization/Aging
Ingredients/BOM
Interaction
010203040506070
LOE Data Acquisition
DB Rationalization
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Key Issues
1. How quickly will databases become obsolete?
2. Why do service-oriented architectures change data persistence beyond recognition?
3. Will any of your products and skills remain relevant?
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Access Changes: Emerging Access Mechanisms
Traditional access mechanisms included requirements such as location and method– Data of interest in DBMSs– Standardized access methods
Emerging access mechanisms are designed around reading data content– XQuery– Search data need not be centralized
Hypertext as an engine of state?
Develop new policies for persistence based on mechanisms other than DBMS
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Access Changes: Center of Gravity Moves Toward Unstructured Data
OLTP and BI(narrow scope)
Compliance, CompetitiveIntelligence(wide scope)
ApplicationTypes
DataDemand Unstructured Data
Structured Data
Percent of corporate informationvalue managed in traditionaldatabases
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Access Changes: Security Rises Above the Database
Web Apps.
YourApp.
CRM
SCM
Enterprise Apps.
ERP
HR
CustomersPartners
Supply Chain
EmployeesContractors
Temps
PrivateNetwork
NOS Directory
Extranet Directory
Internet EAM Engine
AUDIT DB
Identity Administration
User Provisioning/Metadirectory
DataDB
DataDB
ApplicationDirectory
AuthoritativeRepository
YourApp.
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Delivery Changes: Metadata Breaks the Binding
Dynamic metadata repositoriesDynamic decision by applications Applications obtain data "addresses" from services
MetadataServices
Repository
Vocabularies,Meanings,
Associations
Integration Components
Catalog,Registry,Search,
Map
IT Systems Model
SQL Server, Oracle, DB2…
BusinessApplications
XML
MetadataMetadata
DocumentsRich Media
Messaging Web Forms and Portals
Applications
TechnicalMetadata
Common Business Language (Ontology
Model)
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Delivery Changes: Off the Beaten Path, Old Compromises Are Gone
SOA– Implied universal connectivity– No difference in access/delivery of persistent and
ephemeral information– Means that persistence can become implicit and policy-
based
Everything looks ephemeral– Mechanisms federate highly redundant, overlapped and
distributed data for reference information– Transactional information flow is controlled by process
engines that support persistence policy at the macro level– Micro-level policies are implemented in middleware (for
example, queues backed by persistence storage, write through distributed caches)
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Key Issues
1. How quickly will databases become obsolete?
2. Why do service-oriented architectures change data persistence beyond recognition?
3. Will any of your products and skills remain relevant?
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Operational applications will actively locate resources– Range, asset profiles, operational intensity– Data rows do not have to be placed into a static
repository for append or update
Business function challenges business process-based design
Usage Changes: Active Decision Processing
Identify vendors concentrating on the services and policy vision
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Usage Changes: Documentation and Reporting
Documentation moves to an active state– Warning labels– Ingredients/BOM
Reporting becomes an archive activity– Actual data state vs. interpreted data states
Insurance claim status, for example– Workflows transformed from database
tracking to a distributed process engine– Process "state" is examined "in flight"
instead of a representation in a database
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Data Persistence and Policy Layers
Default standard is "static resume" for all activity and controlled by each application using DBMS commandsPersistence becomes a series of reusable policies only, invoking persistence when the application SLA demands it
Persistence DBMS
Reference DBMS
Analytic DBMS
Common Reference
Micro Flow
Macro Flow
Custom
Application Parameters
Application DBMS
DBMS Command Language
Application
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Usage Changes: Policy Enables the Distribution of Data Persistence
Process tracking data disappearsData points to support rules rationalization become the dominant data type– Situational analysis– Definitional parameters
Reporting and analysis dichotomy is more precise– Historic vs. operational reporting– Historic vs. operational analysis
Policy-based persistence
Primary database deployment will shift to master data, metadata and historic data repositories by 2011 (0.6probability).
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Persistence becomes an attribute of all parts of the system, not just concentrated in the databasePolicy-based persistence is the norm, and mechanisms and architecture reflect the various policy scopes
– Classic "database" fits only the historic scope
Federation succeeds over limited domains– Continues to be challenged by the "flood" of more data used
more often
Persistence Becomes a Policy
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Market Impact: Winners, Losers and Pervasive Change
BI
Applications
Integration
DBMS
Declines in relevance, size ($) and percent of
revenue for major vendors (IBM,
Microsoft, Oracle); smaller DBMS vendors
exit the market
Significant growth as the focus shifts to
interoperability, the need to merge,
cleanse and transform data
remains
Simplification of composite application deployment, domain-
specific expertise becomes key differentiator
Line between BI and applications is
further blurred, new types of BI are possible, all BI
becomes real time
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Current DBA skills become less relevant– Architectural skills for information
representation remain valid– Technology skills will decline in value
(e.g., DBMS-specific knowledge)By 2009, the DBA will split into two roles (0.8 probability)– Repository administrator — catalog of
sources, data-location expert including layout and model
– Data service administrators —knowledgeable of statistics gathered, system reliabilities, data reliabilities, physical and logical data models
Maintenance Fades:Utilization Knowledge Is Dominant
DBA
DSA
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Usage
Access
Delivery
Storage
Business Is Function, Not Sequence
Common Ref.
Micro Flow
Macro Flow
Custom
Apps. Parms
In
Out.
Speed of process execution– Demands data access happen in near
real timeProcess-centric automation models, shifting from task-centric to process-centric
– Broader representations of state, transferred less often
Distribution of information: Information is highly distributed
– Mechanisms that can treat the distributed engine as an entity for data management Application
Database CommandLanguage
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Recommendations
User Organizations– Develop new applications for DBMS independence– Develop new policies for persistence based on other
mechanisms besides DBMS– Create clear service levels for persistence of information when
designing systems – Foster overlap between middleware and DBA skills– Identify vendors concentrating on the services and policy vision
Vendors– Eliminate database command language dependencies in
applications– Acquire or partner with domain specialists– Become first or best in a targeted domain of data management– Enable interoperability with other domain specialists