Cassandra Summit 2015

I attended my first Cassandra Summit 2015 this week at the Santa Clara convention center. I was quite surprised to see more than 6000 people attend this event, much bigger than last year (2000 attendees) with 130 sessions. It was a proof to the growing popularity of Cassandra’s NoSQL database platform. CTO and cofounder  Jonathan Ellis (formerly from Rackspace) described new release 2.2 and 3.0 functions.

With its major addition of JSON support in 2.2, Cassandra basically eliminated the difference with MongoDB. They have their own query language called CQL, an SQL-like construct. Now with JSON support, the developer community will see some big advantages. They have functions like collections, udf (user defined types), and deeper nesting. Release 3.0 will see a brand new storage engine, a vast improvement to their previous key-value store engine with better space efficiency. Release 3.0 will include materialized views. Bragging about their fast performance and efficient distributed database functionality, Jonathan joked about MongoDB as the “snapchat for databases” (a reference to occasional data loss because of weak consistency). He emphasized three key elements: availability (onstage they dramatized the shutting down of many nodes in two data centers with Cassandra still running), scale, and performance (both read and write).

However, when it comes to streaming analytics, one Cassandra user explained how he combined Spark, Kafka, and Cassandra to achieve the same – a non-trivial programming feat. Cassandra CEO Billy Bosworth emphasized that they solve the transaction workload problem (always-on) and not geared for analytics. I understood that two key customers are Apple running their iTune application on Cassandra and Netflix. Majority of use cases were web-centric applications where speed and scale are key requirements. Several case studies indicated customers replacing MySQl with Cassandra.

In a panel discussion on monetizing open source software, the comment was made that Cassandra is foundational and customers are happy to pay for the fast performance and scale using their enterprise edition. In that sense, they are different than the RedHat model.

It was an interesting experience to see a new-generation database product gaining wider acceptance.

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