A Morning with MongoDB - Helsinki

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• #MongoDBHelsinki

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

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

Business Development Director, 10gen

#MongoDBHelsinki

Industry

Database Evolution #1Database Evolution #1

Database Evolution #2Database Evolution #2

Database Evolution #3Database Evolution #3

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.

What Values, For Which Audience?

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NoSQL

What Values, For Which Audience?

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Databases in the Future

Why MongoDB

European Clients

• 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

Content Management Operational Intelligence

E-Commerce User Data Management High Volume Data Feeds

MongoDB Use Cases

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

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

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

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

What Values, For Which Audience?

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• Automation & ScalingShardingHigh-Availability

• Resilience, DRWrite-Concerns give granular control, across data-centers

For Operations

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

Coffee

Business Development Director, 10gen

#MongoDBHelsinki

• 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

• 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

Prize Draw

VIP Ticket to MongoDB London