Great for analytics in association with Hadoop MapReduce
It can handle very large volumes of data
Supports scaling out in coordination with Hadoop file system even on commodity hardware
Fault tolerance
License free
Very flexible on schema design/no fixed schema
Can be integrated with Hive for SQL-like queries, which is better for DBAs who are more familiar with SQL queries
Auto-sharding
Auto failover
Simple client interface
Row-level atomicity, that is, the PUT operation will either write or fail
The following are some missing aspects:
Single point of failure (when only one HMaster is used)
No transaction support
JOINs are handled in MapReduce layer ...
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