Robbie Strickland got involved in the Apache Cassandra project in 2010, and he initially went into production with the 0.5 release. He has made numerous contributions over the years, including his work on drivers for C# and Scala, and multiple contributions to the core Cassandra codebase. In 2013, he became the very first certified Cassandra developer, and in 2014, DataStax selected him as an Apache Cassandra MVP. While this is Robbie's first published technical book, he has been an active speaker and writer in the Cassandra community and is the founder of the Atlanta Cassandra Users Group. Other examples of his writing can be found on the DataStax blog, and he has conducted numerous webinars and spoken at many conferences over the years.

Apache Cassandra is a massively scalable, peer-to-peer database designed for 100 percent uptime, with deployments in the tens of thousands of nodes supporting petabytes of data. This book offers readers a practical insight into building highly available, real-world applications using Apache Cassandra.

The book starts with the fundamentals, helping you to understand how the architecture of Apache Cassandra allows it to achieve 100 percent uptime when other systems struggle to do so. You'll have an excellent understanding of data distribution, replication, and Cassandra's highly tunable consistency model. This is followed by an in-depth look at Cassandra's robust support for multiple data centers, and how to scale out a cluster. Next, the book explores the domain of application design, with chapters discussing the native driver and data modeling. Lastly, you'll find out how to steer clear of common antipatterns and take advantage of Cassandra's ability to fail gracefully.

What you will learn:

Understand how the core architecture of Cassandra enables highly available applications

Use replication and tunable consistency levels to balance consistency, availability, and performance

Set up multiple data centers to enable failover, load balancing, and geographic distribution

Add capacity to your cluster with zero down time

Take advantage of high availability features in the native driver

Create data models that scale well and maximize availability

Understand common anti-patterns so you can avoid them

Keep your system working well even during failure scenarios