Is Hadoop used for OLAP?

Is Hadoop good for OLAP?

OLAP on Hadoop solves the problems of speed and scale associated with Big Data. It involves creating multi-dimensional cubes on massive volumes of data using the unlimited storage and processing power of Hadoop. These cubes can serve complex queries instantly and enable quick analysis of Big Data.

Which database is used for OLAP?

Different OLTP databases can be the source of aggregated data for OLAP, and they may be organized as a data warehouse. OLTP, on the other hand, uses a traditional DBMS to accommodate a large volume of real-time transactions.

Is Hive suitable for OLAP?

Apache Hive is mainly used for batch processing i.e. OLAP and it is not used for OLTP because of the real-time operations of the database. Instead, hbase is extensively used for transactional processing wherein the response time of the query is not highly interactive i.e. OLTP.

Is HBase OLAP or OLTP?

HBase (a NoSQL variant) is designed to be an OLTP engine, allowing an architecture of high-volume transactional operations – think messaging platforms with constant messages being exchanged between users or transactions being generated in a financial system.