1. Dec, 7 2011
Real NoSQL
Applications in the
Enterprise Today.
Apache
Cassandra
Jonathan Ellis, CTO DataStax

2. Today’s Database Challenge

3. Navigating the NoSQL waters
 Distributed
 Horizontally scalable
 Eventually consistent
 Non-relational
 Column store
 Document stores
 Key-value
 Graph
 … and more

4. Cassandra: the best for “big data”
 Elegant architecture
 Operational flexibility
 Industry-leading performance
 Youshould be using Cassandra for
applications requiring
 high-performance, realtime queries
 scalability past one machine
 bulletproof reliability

5. Bigtable, 2006
Dynamo, 2007
OSS, 2008
Incubator, 2009
TLP, 2010
1.0, October 2011

6. Cassandra Highlights
 Multi-master, multi-DC
 Linearly scalable
 Larger-than-memory datasets
 High performance
 Full durability
 Integrated caching
 Tuneable consistency

7. Performance
A single four-core machine; one million inserts + one million updates

9. The Cassandra Difference
Scalable
Operational
Cost
Performance
Ease
Effective
Cassandra
*
✔
✔
✔
Oracle Exadata
✔
✔
✖
MySQL
✖
✔
✔
MongoDB
✖
✔
✔
Sharding
✔
✖
✔
HBase
✔
✖
✔
*
And when it comes to Performance, we’re unmatched.

10. “With Cassandra, we get better business
agility, and we don’t have to plan capacity in
advance, we don’t need to ask permission of
other people to build things for us, and we
don’t worry about running out of space or
power.”
 Adrian Cockcroft, Cloud Architect

11. Netflix’s problems
 Could not build datacenters fast enough
 Made decision to go to cloud (AWS)
 Cassandra on AWS is a key infrastructure
component of its globally distributed
streaming product.
 Applications include Netflix’s subscriber
system, AB testing, and viewing history
service (including positions at which
members stopped watching a streaming
program).

12. Netflix on Cassandra TODO
 Fast
 Cheap
 Scalable
 Flexible
 No SPOF

13. “Without Cassandra, our engineers would’ve
had to create something that could scale to
our needs, that would’ve prevented us from
focusing on building product and solving
problems for Backupify’s users, which are far
more important tasks.”
 Matt Conway, VP Engineering

14. Backupify’s problem
 Cloud-based utility that enables
businesses and consumers to backup,
search and restore the content of popular
online applications such as Google Apps,
Gmail, Facebook, Twitter, and Blogger
 Needs:
 Horizontal scaling
 Ability to handle high write loads
 Elasticity with no manual sharding

15. Backupify on Cassandra
 Ease of scale enabled engineers to focus
on building great applications
 DataStax OpsCenter made it easy to
monitor the health and perf of their cluster
 Reliable, redundant and scalable low-
balance data storage helped eliminate
down-time
 Ability to offer both backup and storage,
but also analysis of data eventually

16. “You can seamlessly add new nodes and
expand your total capacity without
deteriorating the performance of the data
store. Cassandra has allowed us to scale very
effectively.”
 Harry Robertson, Tech Lead

17. Ooyala’s problem
 Ooyala provides a suite of technologies
and services that support content owners
in managing, analyzing and monetizing
the digital video they publish online
 Needs:
 Elasticity,to respond to spikes in data scale
 Ability to respond to increasingly
sophisticated analytic needs of customers

18. Ooyala on Cassandra
 Classic “Big Data” problem did not require
re-architecting
 Application agility was enabled –
developers spend time building cool apps,
not figuring out how to scale
 Enabled more powerful and granular
analytics to their customers

19. “Cassandra has allowed us to build bigger
features faster and more reliably, while using
less money and without needing to expand
our staff.”
 Kyle Ambroff, Sr. Engineer

20. Formspring’ problem
 Usersof Formspring engage with and learn
more about each other by asking and
responding to questions. With close to 4B
responses in the system and 30M unique
users, they needed:
 To support explosive growth
 To seamlessly syndicate user content
 To avoid sharding
 Application flexiblity

21. Formspring on Cassandra
 No sharding needed – just add nodes to
scale
 Performance – the popular users with
many followers saw no speed reduction.
 No more memcached!
 Flexibility of a schema-optional
architecture is very developer friendly

22. Why DataStax?
DataStax delivers database products and services
based on Apache Cassandra from experts who are
at the forefront of today's data revolution.
Database Software & Tools
Support & Services
 DataStax Enterprise
 Production Support
 DataStax Community
 Consultative Help
 DataStax OpsCenter
 Professional Training
 Drivers & Connectors
 Online Documentation

23. DataStax Overview
 Founded in April 2010
 Commercial leader in Apache Cassandra™, the popular
open-source “big data” database
 Headquartered in San Francisco Bay area
 100+ customers
 35+ employees (split between San Fran and Austin)
 Home to Apache Cassandra Chair & most committers
 Secured $11M in Series B funding in Sep 2011

24. DataStax Value
 The simplest way to get started with Apache
Cassandra: DataStax Community Edition
 A smart, integrated platform that provides
Analytics and Real-Time capabilities in the
same database, without any resource
contention: DataStax Enterprise
 The backing of the Cassandra Experts

25. 100+ customers

26. DataStax Enterprise
1. DataStax Enterprise
Database Server
2. OpsCenter
Enterprise
Management
solution
3. Expert production
support &
consultative
services

27. Enterprise Database Server
Enterprise-class database built to handle
today’s big-data needs in a cost-effective, easy,
and reliable way.
 Leverages resources on-premise or in the
cloud
 Guarantees uptime with a master-less
distributed architecture
 Allows for fast application changes via
flexible schemas
2 3
 Handles structured, semi-structured, and Real-Time
unstructured data
Replication
1 4
 Provides advanced security
 Eliminates the need for separate analytics Analytics
system
6 5

28. OpsCenter Enterprise
OpsCenter Enterprise supplies management,
monitoring, and control over DataStax Enterprise
 Visual, browser-based user  Proactive alerts that warn
interface
of impending issues
 Administration tasks  Built-in external
carried out in point-and- notification abilities
click fashion
 Allows for visual rebalance
of data across a cluster
when new nodes are added

29. Expert Production Support
DataStax Enterprise includes production support
and consultative services from the Cassandra
experts.
 Support service level
agreements that range from
business hours to 24x7x365
 Consultative support for
assistance on architecture,
design, and tuning
 Certified quarterly service
packs
 Hot-fix support

30. DataStax Enterprise Compared
Scalable
Operational
Cost
Real-Time +
Performance
Ease
Effective
Analytics
DataStax Enterprise
✔
✔
✔
✔
Oracle Exadata
✔
✔
✖
✔
MySQL
✖
✔
✔
✖
MongoDB
✖
✔
✔
✖
Sharding
✔
✖
✔
✖
HBase
✔
✖
✔
✖
Oracle NoSQL DB
✔
✖
? ✔

31. DataStax – Your One-Stop Shop
 DataStax Enterprise and Community Editions
 Professional Training, Expert Consulting
 Documentation and Dev Center
 http://www.datastax.com/docs
 http://www.datastax.com/dev
 Whitepapers, Case Studies, FAQ’s and more
 http://www.datastax.com/resources/whitepapers
 http://www.datastax.com/resources/casestudies
Thank you!