The Future Of Big Data

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A high level overview of common Cassandra use cases, adoption reasons, BigData trends, DataStax Enterprise and the future of BigData given at the 7th Advanced Computing Conference in Seoul, South …

A high level overview of common Cassandra use cases, adoption reasons, BigData trends, DataStax Enterprise and the future of BigData given at the 7th Advanced Computing Conference in Seoul, South Korea

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  • 1. Cassandra 1.0The Future Of Big DataMatthew F. Dennis // @mdennis7th Advanced Computing ConferenceSeoul, South KoreaFebruary 15th, 2012
  • 2. Cassandra Job Trends (indeed.com)
  • 3. Cassandra Job Trends (indeed.com)
  • 4. “Big Data” Job Trends (indeed.com)
  • 5. Big Data
  • 6. Why People Choose Cassandra True Multi­DC Support Linearly scalable Larger­than­memory datasets Best­in­class performance (not just for writes!) Fully durable Integrated caching Tuneable consistency No single point of failure (SPOF)
  • 7. Common Cassandra Use Cases Time Series  Sensor Data Messaging Ad Tracking Financial Market Data User Activity Streams Fraud Detection / Risk Analysis Anything Requiring: linear scale + high performance + global availability
  • 8. “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
  • 9. 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 pause/resume).
  • 10. Netflix on Cassandra Fast Cheap Scalable Flexible No SPOF
  • 11. Scale Horizontally http://www.datastax.com/1-million-writesClient Writes Per Second Number Of Nodes
  • 12. “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
  • 13. Backupify’s problemCloud­based 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
  • 14. Backupify on CassandraEase of scale enabled engineers to focus on building great applicationsDataStax OpsCenter made it easy to monitor the health and performance of their clusterReliable, redundant, scalable and cheap data  storage helped eliminate down­timeAbility to offer both backup and storage, but   also analysis of data in the future
  • 15. “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
  • 16. Ooyala’s problemOoyala provides a suite of technologies and services that support content owners in managing, analyzing and monetizing the digital video they publish online
  • 17. Ooyala on CassandraClassic “Big Data” problem did not require re­architectingEnabled Application agility – developers spend time building cool apps, not figuring out how to scaleEnabled more powerful and granular analytics for their customers
  • 18. Some More Cassandra Users http://www.datastax.com/cassandrausersFinancialSocial MediaAdvertisingEntertainmentEnergyE­TailHealth CareInfrastructureGovernment
  • 19. Big Data
  • 20. The evolution of Analytics Analytics + Realtime
  • 21. The evolution of Analytics replication Analytics Realtime
  • 22. The evolution of Analytics ETL Analytics Realtime
  • 23. DataStax Enterprise re-unifies realtime and analytics
  • 24. realtime and analytics
  • 25. Portfolio Demo dataflowPortfolios PortfoliosHistorical Prices Live Prices for todayIntermediate ResultsLargest loss Largest loss
  • 26. Operations“Vanilla” Hadoop Many pieces to setup, monitor, backup, and maintain (NameNode, SecondaryNameNode, DataNode, JobTracker, TaskTracker, Zookeeper,  Region Server, ...) Single points of failureDataStax Enterprise Single simplified system Self­organizes based on workload Peer to peer JobTracker failover No additional Cassandra config
  • 27. Monitoring Cassandra (OpsCenter)
  • 28. Q?Matthew F. Dennis // @mdennishttp://slideshare.net/mattdennis