title: “MongoDB”, type: meetup presentation”, speaker...
Transcript of title: “MongoDB”, type: meetup presentation”, speaker...
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{ title: “MongoDB”, type: “meetup presentation”, speaker: { name: “Izsák Tamás”, company: “APPWORKS” } location: “BudapestNoSQL”, date: “2016-03-23T20:15:00.000Z” }
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Relational Database Challenges
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Relational Database Challenges
Data Types
• Unstructured data
• Semi-structured data
• Polymorphic data
Volume of Data
• Petabytes of data
• Trillions of records
• Millions of queries per second
Agile Development
• Iterative
• Short development cycles
• New workloads
New Architectures
• Horizontal scaling
• Commodity servers
• Cloud computing
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MongoDB Solution
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The leading NoSQL database
Document Database
Open-Source
General Purpose
MongoDB
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mongoDB
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RDBMS
Agility
MongoDB
{
_id : ObjectId("4c4ba5e5e8aabf3"),
employee_name: "Dunham, Justin",
department : "Marketing",
title : "Product Manager, Web",
report_up: "Neray, Graham",
pay_band: “C",
benefits : [
{ type : "Health",
plan : "PPO Plus" },
{ type : "Dental",
plan : "Standard" }
]
}
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Better Data Locality
Performance
In-Memory Caching In-Place Updates
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Scalability
Auto-Sharding
• Increase capacity as you go
• Commodity and cloud architectures
• Improved operational simplicity and cost visibility
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High Availability
• Automated replication and failover
• Multi-data center support
• Improved operational simplicity (e.g., HW swaps)
• Data durability and consistency
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Sharding and Replication
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Shell Command-line shell for interacting directly with database
Shell and Drivers
Drivers Drivers for most popular programming languages and frameworks
> db.collection.insert({product:“MongoDB”,
type:“Document Database”})
>
> db.collection.findOne()
{
“_id” :
ObjectId(“5106c1c2fc629bfe52792e86”),
“product” : “MongoDB”
“type” : “Document Database”
}
Java
Python
Perl
Ruby
Haskell
JavaScript
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MongoDB Architecture
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MongoDB
What we HAVE • Document-Oriented storage • Fast In-Place Updates • Full Index Support • Replication & High Availability • Auto-Sharding • Querying (aggregation framework) • Map/Reduce
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MongoDB
What we DO NOT have • Transactions • Joins
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MongoDB
Document Store RDBMS MongoDB
Database Database
Table, View Collection
Row Document (JSON, BSON)
Column Field
Index Index
Join Embedded Document
Foreign Key Reference
Partition Shard
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MongoDB
Document Store RDBMS MongoDB
Database Database
Table, View Collection
Row Document (JSON, BSON)
Column Field
Index Index
Join Embedded Document
Foreign Key Reference
Partition Shard
> db.user.findOne({age:39}) { "_id" : ObjectId("5114e0bd42…"), "first" : "John", "last" : "Doe", "age" : 39, "interests" : [ "Reading", "Mountain Biking ] "favorites": { "color": "Blue", "sport": "Soccer"} }
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MongoDB
Relational modell
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MongoDB
MongoDB
{ "patient_id": "1177099", "first_name": "John", "last_name": "Doe", "dob": "2000-01-25", "gender": "Male", "blood_type": "B+", "allergies": ["Nuts", "Penicillin", "Pet Dander"], "current_medications": [{"name": "Zoloft", "dosage": "2mg", "frequency": "daily", "route": "orally"}], "complaint" : [{"entered": "2000-11-03", "onset": "2000-11-03", "prob_desc": "", "icd" : 250.00, "status" : "Active"}, {"entered": "2000-02-04", "onset": "2000-02-04", "prob_desc": "in spite of regular exercise...", "icd" : 401.9, "status" : "Active"}], "diagnosis" : [{"visit" : "2005-07-22" , "narrative" : "Fractured femur", "icd" : "9999", "priority" : "Primary"}, {"visit" : "2005-07-22" , "narrative" : "Type II Diabetes", "icd" : "250.00", "priority" : "Secondary"}] }
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MongoDB
Focus on data storage
Focus on data use
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MongoDB
What answers do I have?
What questions do I have?
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