If you are working on hadoop then we expect you to be familiar with HBase. May be you think HBase to be more popular than it is, but its time may already have passed. The question is why?
Why has HBase failed to match the popularity of Hadoop, given its pole position with the popular big data platform?
Most of the Hadoop expert expected HBase to rival MongoDB and Cassandra, its narrow utility and inherent complexity have hobbled its popularity and allowed other databases to claim the big data crown.
According to DB- Engines, which tracks database popularity across a number of metrics(Google searches, job postings, forum mentions), HBase was on a tear for years, keeping pace with the top NoSQL peers. Early in 2015, however, HBase started to slide, even as MongoDB and Cassandra kept rising.
Another reason for its unpopularity is making big data hard
Server Density CEO David Mytton, for one, argues that HBase is “Pain to deploy and run.” Another industry insider, who preferred not to be named, was more emphatic, decreeing that HBase is “impossible to run.”
Two years ago Infoworld’s Rick Grehan pointed to the inherent difficulty in clustering and troubleshooting HBase, not to mention of the difficulties related to its schema. As other big data tech has emerged to extend or supersede Hadoop, HBase’s pole position with Hadoop has come to mean less and less, even as the need for the general -purpose NoSQL databases has come to matter more and more. By not evolving to embrace a biggerer universe of workloads and not making it easier to use HBase, it continues to play a part in NoSQL, but not the dominant one it once could claim.