HBase

HBase is a data model that is similar to Google’s big table designed to provide quick random access to huge amounts of structured data.

Features

• 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 

HBase Architectural Components

Physically, HBase is composed of three types of servers in a master slave type of architecture. Region servers serve data for reads and writes. When accessing data, clients communicate with HBase RegionServers directly. Region assignment, DDL (create, delete tables) operations are handled by the HBase Master process. Zookeeper, which is part of HDFS, maintains a live cluster state.
The Hadoop DataNode stores the data that the Region Server is managing. All HBase data is stored in HDFS files. Region Servers are collocated with the HDFS DataNodes, which enable data locality (putting the data close to where it is needed) for the data served by the RegionServers. HBase data is local when it is written, but when a region is moved, it is not local until compaction.
The NameNode maintains metadata information for all the physical data blocks that comprise the files.