Download - A Morning with MongoDB - Helsinki
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Morning with MongoDB Morning with MongoDB
wifi: sodexo12
• #MongoDBHelsinki
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Business Development Director, 10gen
#MongoDBHelsinki
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10gen Overview
10gen is the company behind MongoDB – the leading NoSQL database
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10gen Overview
170+employees
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10gen Overview
500+ customers
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10gen Overview
$73Min funding from top investors
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Leading Organizations Rely on MongoDB
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Global MongoDB Community
41,000+ 41,000+ Monthly Unique DownloadsMonthly Unique Downloads24,000+ 24,000+ Online Education RegistrantsOnline Education Registrants12,000+ 12,000+ MongoDB User Group MembersMongoDB User Group Members10,000+ 10,000+ Annual MongoDB Days AttendeesAnnual MongoDB Days Attendees
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mongoDB Adoption
Resource User Data Management
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Business Development Director, 10gen
#MongoDBHelsinki
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Industry
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Database Evolution #1Database Evolution #1
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Database Evolution #2Database Evolution #2
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Database Evolution #3Database Evolution #3
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Productivity
Costs Cost of database increases• Vertical, not horizontal, scaling• High cost of SAN
Productivity decreases• Needed to add new
software layers of ORM, Caching, Sharding, Message Queue
• Polymorphic, semi-structured and unstructured data not well supported
Organizations are becoming frustrated using a Organizations are becoming frustrated using a RDBMS.RDBMS.
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What Values, For Which Audience?
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NoSQL
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What Values, For Which Audience?
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Databases in the Future
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Why MongoDB
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European Clients
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• Open source, written in C++• Document-oriented Storage
– Based on JSON Documents– Schema-less
• Full featured indexes, query language
• Replication & High Availability• Auto-sharding
MongoDB is a scalable, high-performance NoSQL MongoDB is a scalable, high-performance NoSQL database.database.
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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•Tens of 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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Volume of Data
Volume of Data•Petabytes of data•Trillions of records•Millions of queries per second
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Data Types
Data Types•Unstructured data•Semi-structured data•Polymorphic data
{
_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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Agile Development
Agile Development•Iterative•Short development cycles•New workloads
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Content Management Operational Intelligence
E-Commerce User Data Management High Volume Data Feeds
MongoDB Use Cases
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A need to extract value from existing semi-structured
data sources (social networks etc.)
A fast-growing customer-base required any solution
to be easily scalable
A need to extract value from existing semi-structured
data sources (social networks etc.)
A fast-growing customer-base required any solution
to be easily scalable
Problem
“Selecting MongoDB as our database platform was a no brainer as the technology offered us the flexibility and scalability that we knew we’d need for Priority Moments.”
Andrew Pattinson, Head of Online Delivery
Built around scalability, with auto-sharding features
mongoDB deployment architecture prevents any
single point of failure Geospatial indexing out-of-
the-box enables location-based service delivery
Built around scalability, with auto-sharding features
mongoDB deployment architecture prevents any
single point of failure Geospatial indexing out-of-
the-box enables location-based service delivery
Why MongoDB Priority Moments project is
a strong success Subsequent adoption of
mongoDB by O2 & Telefonica across a large
number of projects
Priority Moments project is a strong success
Subsequent adoption of mongoDB by O2 &
Telefonica across a large number of projects
Impact
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RDBMS architecture constrained their ability to
absorb upstream contributions from users
New features, competitions needed to log data into user
records, requiring schema changes
RDBMS architecture constrained their ability to
absorb upstream contributions from users
New features, competitions needed to log data into user
records, requiring schema changes
Problem
“Relational databases have a sound approach, but that doesn’t necessarily match the way we see our data. mongoDB gave us the flexibility to store data in the way that we understand it as opposed to somebody’s
theoretical view.”Philip Wills, Software Architect
Flexible data model allows for heterogeneous structure Rich query language
preserves functionality System updates with zero
downtime Ease of use, allowing a large
development team to adopt the technology quickly
Flexible data model allows for heterogeneous structure Rich query language
preserves functionality System updates with zero
downtime Ease of use, allowing a large
development team to adopt the technology quickly
Why MongoDB The Guardian has competitive advantage, through enabling social
conversations through the site
Interactive features can be delivered more quickly,
which translates to increased revenues
The Guardian has competitive advantage, through enabling social
conversations through the site
Interactive features can be delivered more quickly,
which translates to increased revenues
Impact
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New Architectures
New Architectures•Horizontal scaling •Commodity servers•Cloud computing
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MongoDB Solution
Document-Oriented Database
Agile Scalable
Best TCO
Summary
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Developer and Ops Savings•Less code•More productive development•Easier to maintain
Hardware Savings•Commodity servers•Internal storage (no SAN)•Scale out, not up
Software and Support Savings•No upfront license – pay for value over time•Cost visibility for usage growth
Best Total Cost of Ownership (TCO)
DB Alternative
Best Total Cost of Ownership (TCO)
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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•Tens of 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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What Values, For Which Audience?
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• Agility / FlexibilitySchema-FreeEasy to get started
• PerformanceOften a significant improvement over RDBMS
• FeaturesRich-Query Language, Aggregation Framework, Map-Reduce
For Developers / Architects
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What Values, For Which Audience?
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• Automation & ScalingShardingHigh-Availability
• Resilience, DRWrite-Concerns give granular control, across data-centers
For Operations
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What Values, For Which Audience?
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For Executives
• Competitive AdvantageFaster time-to-marketAccessible real-time analyticsFlexible (low-risk) deployments
• Commodity InfrastructureLower TCO than proprietary RDBMS
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Coffee
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Business Development Director, 10gen
#MongoDBHelsinki
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• Concurrency: yielding + db level locking
• New aggregation framework
• TTL Collections
• Improved free list implementation
• Tag aware sharding
• Read Preferences
• http://docs.mongodb.org/manual/release-notes/2.2/
2.2 Overview
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• Security– SASL, Kerberos, Additions to privileges and auditing
• Hash-based Sharding• Geospatial Indexing: query intersecting polygons• Aggregation framework: faster and more features• V8, background secondary indexing, replica set
flapping• Distribute non-sharded collections throughout
cluster• MMS running in your own data center (separate)
2.4 Roadmap
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Prize Draw
VIP Ticket to MongoDB London
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