Apache Hive vs HBase: What are the differences?
What is Apache Hive? Data Warehouse Software for Reading, Writing, and Managing Large Datasets. Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.
What is 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.
Apache Hive and HBase are primarily classified as "Big Data" and "Databases" tools respectively.
Apache Hive and HBase are both open source tools. It seems that HBase with 2.91K GitHub stars and 2.01K forks on GitHub has more adoption than Apache Hive with 2.62K GitHub stars and 2.58K GitHub forks.
According to the StackShare community, HBase has a broader approval, being mentioned in 54 company stacks & 18 developers stacks; compared to Apache Hive, which is listed in 27 company stacks and 12 developer stacks.
What is Apache Hive?
What is HBase?
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Why do developers choose Apache Hive?
What are the cons of using Apache Hive?
What are the cons of using HBase?
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The final output is inserted into HBase to serve the experiment dashboard. We also load the output data to Redshift for ad-hoc analysis. For real-time experiment data processing, we use Storm to tail Kafka and process data in real-time and insert metrics into MySQL, so we could identify group allocation problems and send out real-time alerts and metrics.