The document discusses NoSQL, NewSQL, and other database technologies that are emerging to address limitations of relational databases in scaling to meet demands for performance, availability, and flexibility. It provides an overview of different categories of NoSQL databases and NewSQL solutions, and analyzes drivers like scalability, performance, relaxed consistency, agility, and complexity of data that are contributing to adoption of these new database approaches.

1. NoSQL, NewSQL, and Beyond
The answer to SPRAINed relational databases
Matthew Aslett
Research Manager, Data Management and Analytics 1
© 2012 by The 451 Group. All rights reserved

2. 451 Research
 Matthew Aslett
• Research manager, data management and analytics
• With The 451 Group since 2007
• www.twitter.com/maslett
Information Management Commercial Adoption of Open Source
 Operational databases (CAOS)
 Data warehousing  Open source projects
 Data caching  Adoption of open source software
 Event processing  Vendor strategies
© 2012 by The 451 Group. All rights reserved

3. The 451 Group
3
© 2012 by The 451 Group. All rights reserved

4. Relevant reports
 NoSQL, NewSQL and Beyond
• Assessing the drivers behind the development and adoption
of NoSQL and NewSQL databases, as well as data
grid/caching technologies
• Released April 2011
• Role of open source in driving innovation
• sales@the451group.com
© 2012 by The 451 Group. All rights reserved

5. NoSQL, NewSQL and Beyond
NoSQL NewSQL
 New breed of non-relational  New breed of relational
database products database products
 Rejection of fixed table  Retain SQL and ACID
schema and join operations  Designed to meet scalability
 Designed to meet scalability requirements of distributed
requirements of distributed architectures
architectures  Or improve performance so
 And/or schema-less data horizontal scalability is no
management requirements longer a necessity
… and Beyond
 In-memory data grid/cache products
 Potentialprimary platform for distributed data management
© 2012 by The 451 Group. All rights reserved

6. The NoSQL landscape
Key Value Store Graph
•Citrusleaf Document • InfiniteGraph
• HandlerSocket* •RavenDB • Neo4j
• Redis • Riak • MongoDB • DEX
• Voldemort •CouchBase • CouchDB •OrientDB
• Membrain • Mongo Labs • Cloudant •NuvolaBase
• Oracle NoSQL • Mongo HQ • Iris Couch
• Castle •DynamoDB
•RethinkDB • Redis-to-go
•LevelDB • SimpleDB
• Cassandra
• DataStax EE
•Acunu
• HBase • App Engine Datastore -as-a-Service
• Hypertable Big Tables
© 2012 by The 451 Group. All rights reserved

7. The NewSQL ecosystem
-as-a-Service
New databases
•Drizzle •NuoDB
• Xeround •Drizzle • VoltDB •SQLFire
• Tokutek • Akiban • JustOne DB • Translattice
• GenieDB • Clustrix
• Schooner SQL
•ScaleDB •ParElastic • ScaleBase
Storage engines • MySQL Cluster •Continuent •ScaleArc
•Zimory Scale •Galera • CodeFutures
Clustering/sharding
© 2012 by The 451 Group. All rights reserved

8. SPRAINED RELATIONAL DATABASES
Photo credit: Foxtongue on Flickr
http://www.flickr.com/photos/foxtongue/4844016087/
© 2012 by The 451 Group. All rights reserved

9. SPRAIN
Scalability - Hardware economics
 Example project/service/vendor:
• BigTable, HBase, Riak, MongoDB, Couchbase, Hadoop
• Xeround, NuoDB
• Data grid/cache
 Associated use case:
• Large-scale distributed data storage
• Analysis of continuously updated data
• Multi-tenant PaaS data layer
© 2012 by The 451 Group. All rights reserved

10. SPRAIN
Scalability
 Netflix:
• 37X growth in requests Jan 2010-Jan 2011
• “We had to get out of the datacenter business”
 Dachis Group:
• Specifically wanted a horizontally scalable data store
 Spotify:
• Importance (and challenges) of cross-datacenter replication
 Tellybug:
• Peak scalability – mission critical for two hours per week. Elastic
scalability still not solved.
© 2012 by The 451 Group. All rights reserved

11. SPRAIN
Performance – RDBMS limitations
 Example project/service/vendor:
• Hypertable, Couchbase, Riak, Membrain, MongoDB, Redis
• Data grid/cache
• VoltDB, Clustrix
 Associated use case:
• Real time data processing of mixed read/write workloads
• Data caching
• Large-scale data ingestion
© 2012 by The 451 Group. All rights reserved

12. SPRAIN
Performance
 Tellybug:
• Having won the contract to deliver app for Britain’s Got Talent
realised that its MySQL/Django/Python stack couldn’t deliver the
anticipated load
 Spotify:
• Major upgrades without service interruptions, not possible with
sharded SQL databases
 Rackspace:
• Ability to monitor a million different things, ability to withstand the
failure of 1/3 data centers
© 2012 by The 451 Group. All rights reserved

13. SPRAIN
Relaxed consistency - CAP Theorem
 Example project/service/vendor:
• Dynamo, Voldemort, Cassandra, Riak
• Amazon DynamoDB
 Associated use case:
• Multi-data center replication
• Service availability
• Non-transactional data off-load
© 2012 by The 451 Group. All rights reserved

14. SPRAIN
Relaxed consistency
 Netflix:
• “We value availability over consistency. We don’t need full
consistency.”
 Tellybug:
• Soft production data – the ability to ignore failures
• Spotify:
• Flexibility to combine different consistency levels for different
column families in a single application
© 2012 by The 451 Group. All rights reserved

15. SPRAIN
Agility - polyglot persistence, schema-less
 Example project/service/vendor:
• MongoDB, CouchDB, Cassandra, Riak
• Google App Engine, SimpleDB,
 Associated use case:
• Mobile/remote device synchronization
• Agile development
• Data caching
© 2012 by The 451 Group. All rights reserved

16. SPRAIN
Agility
 Tellybug:
• Had 4-5 weeks to ship a production system to meet contract
• Ability to re-build entire infrastructure from scratch in 10-15 mins
 Netflix:
• Single SQL database had to be brought down to change the schema.
• Put the logic into the Web services and employ distributed key
stores to enable agile development and schema changes
 Spotify:
• Cassandra is a platform for quickly developing new applications
© 2012 by The 451 Group. All rights reserved

17. SPRAIN
Intricacy – volume, velocity, variety
 Example project/service/vendor:
• Neo4j, GraphDB, InfiniteGraph
• Apache Cassandra, Hadoop, Riak
• VoltDB, Clustrix
 Associated use case:
• Social networking applications
• Geo-locational applications
• Configuration management database
© 2012 by The 451 Group. All rights reserved

18. SPRAIN
Intricacy
 Dachis Group:
• Combining social media data for 2,000 brands with sentiment,
relationship, conversations, social graph
 Spotify:
• More than half a billion playlists, about 10 thousand requests per
second at peak
 Rackspace:
 One row per customer with thousands of columns – potentially
millions of columns
 Tellybug:
• Ability to cope with 10,000 interactions/sec and integrate that with
the social graph for thousands of concurrent users
© 2012 by The 451 Group. All rights reserved

19. SPRAIN
Necessity - open source
 The failure of existing suppliers to address emerging
requirements
 Example projects:
• BigTable: Google
• Dynamo: Amazon
• Cassandra: Facebook
• HBase: Powerset
• Voldemort: LinkedIn
• Hypertable: Zvents
• Neo4j: Windh Technologies
© 2012 by The 451 Group. All rights reserved

20. SPRAIN
Necessity
 Spotify:
• Created own backup and restore technology
 Rackspace:
• Distributed secondary indexing, blob storage, many other projects
 Tellybug:
• Created sharded counter in memcached, wrote several tools to
figure out closeness to the ‘truth’
 Netflix:
• Developed multiple tools including multi-datacenter replication,
automated configuration and backup, provisioning interface etc
© 2012 by The 451 Group. All rights reserved

21. Relevant reports
 MySQL, NoSQL and NewSQL
• Assessing the competitive dynamic between the MySQL
ecosystem, NoSQL and NewSQL technologies
• Due May 2012
• Including market sizing of the three
database segments
• Survey of 200+ database users
• sales@the451group.com
© 2012 by The 451 Group. All rights reserved

22. Thank you. Questions? Comments?
matt.aslett@451research.com
@maslett
© 2012 by The 451 Group. All rights reserved