That is, it provides a fault-tolerant way of storing large quantities of sparse data (small amounts of information caught within a large collection of empty or unimportant data, such as finding the 50 largest items in a group of 2 billion records, or finding the non-zero items representing less than 0.1% of a huge collection).

HBase features compression, in-memory operation, and Bloom filters on a per-column basis as outlined in the original Bigtable paper.

HBase runs on top of HDFS and is well-suited for fast read and write operations on large datasets with high throughput and low input/output latency.

[4][5] Unlike relational and traditional databases, HBase does not support SQL scripting; instead the equivalent is written in Java, employing similarity with a MapReduce application.

[6] Apache HBase began as a project by the company Powerset out of a need to process massive amounts of data for the purposes of natural-language search.