HBase

• May 19, 2015
• Girikon

Main point: Billions of rows X millions of columns

Key Features:

• Modeled after Google’s BigTable
• Uses Hadoop’s HDFS as storage
• Map/reduce with Hadoop
• Query predicate push down via server side scan and get filters
• Optimizations for real time queries
• A high performance Thrift gateway
• HTTP supports XML, Protobuf, and binary
• Jruby-based (JIRB) shell
• Rolling restart for configuration changes and minor upgrades
• Random access performance is like MySQL
• A cluster consists of several different types of nodes

Best used: Hadoop is probably still the best way to run Map/Reduce jobs on huge datasets. Best if you use the Hadoop/HDFS stack already.

Examples: Search engines. Analysing log data. Any place where scanning huge, two-dimensional join-less tables are a requirement.
Regards,
Alok In case you need Certified Salesforce Consultant for any Salesforce related work, then please feel free to reach out to sales@girikon.com