Case Study: Netflix

Case Study NetflixDownload the Netflix Case Study

“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 Netflix

Netflix Personalizes Viewing for Over 50 Million Customers with DataStax

Industry: Streaming Media

Netflix, the world’s leading subscription service for movies and TV, launched in 1997 as a provider of DVDs by mail. However, since it launched its “Watch Instantly” streaming delivery service in 2007, the Los Gatos, Calif., company has steadily shifted resources toward the streaming model, since it offers benefits to both the business and to customers (no postage costs or delivery wait times).

At the same time, the company considered the data and storage demands that streaming media would require. (DVDs require warehouse storage – streaming movies require storage of information.)

“We had a single data center, which meant we had a single point of failure,” explains Adrian Cockcroft, cloud architect at Netflix. “We were approaching limits on traffic and capacity. Now that people can watch Netflix streaming programming from their phones, from Wii devices, Roku boxes and many others, the demand for availability increases all the time. We have more customers every quarter, more customers are using streaming, and they’re using streaming at a greater rate.”


  • Affordable capacity to store and process immense amounts of data (more than 2.1 billion reads and 4.3 billion writes per day)
  • Single point of failure with Oracle’s legacy relational architecture
  • Achieving business agility for international expansion


  • DataStax Enterprise delivers a persistent datastore, 100% uptime and cost effective scale across multiple data centers
  • DataStax expert support


  • DataStax delivers a throughput of more than 10 million transactions per second
  • Effortless creation/management of new data clusters across various regions
  • Capture of every detail of customer viewing and log data