* Linear and modular scalability. * Strictly consistent reads and writes. * Automatic and configurable sharding of tables * Automatic failover support between RegionServers. * Convenient base classes for backing Hadoop MapReduce jobs with Apache HBase tables. * Easy to use Java API for client access. * Block cache and Bloom Filters for real-time queries. * Query predicate push down via server side Filters * Thrift gateway and a REST-ful Web service that supports XML, Protobuf, and binary data encoding options * Extensible jruby-based (JIRB) shell * Support for exporting metrics via the Hadoop metrics subsystem to files or Ganglia; or via JMX

* Fault Tolerant - Data is automatically replicated to multiple nodes for fault-tolerance. Replication across multiple data centers is supported. Failed nodes can be replaced with no downtime. * Performant - Cassandra consistently outperforms popular NoSQL alternatives in benchmarks and real applications, primarily because of fundamental architectural choices. * Decentralized - There are no single points of failure. There are no network bottlenecks. Every node in the cluster is identical. * Durable - Cassandra is suitable for applications that can't afford to lose data, even when an entire data center goes down. * You're in Control - Choose between synchronous or asynchronous replication for each update. Highly available asynchronous operations are optimized with features like Hinted Handoff and Read Repair. * Elastic - Read and write throughput both increase linearly as new machines are added, with no downtime or interruption to applications. * Proven - Cassandra is in use at Constant Contact, CERN, Comcast, eBay, GitHub, GoDaddy, Hulu, Instagram, Intuit, Netflix, Reddit, The Weather Channel, and over 1500 more companies that have large, active data sets.