Difference between Hive and HBase ?

Difference between Hive and HBase ?


  • Hive is a datawarehousing package built on the top of Hadoop. It is mainly used for data analysis. It generally target towards users already comfortable with Structured Query Language (SQL).
  • It is similar to SQL and called Hive Query Language (HQL).
  • Hive manages and queries structured data. Moreover, hive abstracts complexity of Hadoop. It does not support
    • Not a full database.
    • Not a real time processing system.
    • Not SQL-92 compliant.
    • Does not provide row level insert, updates or deletes.
    • Doesn’t support transactions and limited sub-query support.
    • Query optimization in evolving stage.


  • HBase is a column-oriented database management system that runs on top of Hadoop Distributed File System (HDFS).
  • It is well suited for sparse data sets, which are common in many Big Data use cases.
  • It is an opensource, distributed database developed by Apache software foundations.
  • Initially, it was named Google Big Table, afterwards it was re-named as HBase and is primarily written in Java.
  • It can store massive amount of data from terabytes to petabytes.
  • It is built for low-latency operations and is used extensively for read and write operations.
  • It stores large amount of data in the form of tables.
Difference between HIVE and HBASE

Difference between HIVE and HBASE

Hive is a query engine. Data storage particularly for unstructured data.
Mainly used for batch processing. Extensively used for transactional processing.
Not a real time processing. Real-time processing.
Only for analytical queries. Real-time querying.
Runs on the top of Hadoop. Runs on the top of HDFS (Hadoop distributed file system).
Apache Hive is not a database. It support NoSQL database.
It has schema model. It is free from schema model.
Made for high latency operations. Made for low level latency operations.

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