Hadoop vs HBase: What are the differences?
Hadoop: Open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage; HBase: The Hadoop database, a distributed, scalable, big data store. Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
Hadoop and HBase belong to "Databases" category of the tech stack.
"Great ecosystem" is the primary reason why developers consider Hadoop over the competitors, whereas "Performance" was stated as the key factor in picking HBase.
Hadoop and HBase are both open source tools. Hadoop with 9.26K GitHub stars and 5.78K forks on GitHub appears to be more popular than HBase with 2.91K GitHub stars and 2.01K GitHub forks.
Airbnb, Uber Technologies, and Spotify are some of the popular companies that use Hadoop, whereas HBase is used by Pinterest, HubSpot, and Yammer. Hadoop has a broader approval, being mentioned in 237 company stacks & 127 developers stacks; compared to HBase, which is listed in 54 company stacks and 18 developer stacks.
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