Is Hive designed for OLAP?

Is Hive used for ETL?

Hive is a powerful tool for ETL, data warehousing for Hadoop, and a database for Hadoop.

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.

Can Hive be used in OLTP system?

No Hive does not provide insert and update at row level. So it is not suitable for OLTP system.

Is Hadoop used for OLAP?

Hadoop is an OLAP. Hadoop is neither OLAP nor OLTP. All above are true statements. Since we use Hadoop to process the analysis of big data & this is done by batch wise on historical data which is loaded in the HDFS (Hadoop distributed file system).

What is OLAP in hive?

OLAP: Hive is designed for OLAP (Online Analytical Processing). Client application: Hive can support client applications written in PHP, Python, Java, C++ and Ruby. Rule Based Optimizer: Hive has a rule based optimizer for optimizing logical plans.

Does Apache Hive support OLTP?

Apache Hive doesn’t support online transaction processing (OLTP) but Online Analytical Processing (OLAP) is supported. Hive does not support update and delete operation on tables. Subqueries are not supported. The latency in the apache hive query is very high.

Why do we use hive in Hadoop?

Since we store Hive data on HDFS so fault tolerance is provided by Hadoop. We can use a hive for data mining, predictive modeling, and document indexing. Apache Hive doesn’t support online transaction processing (OLTP) but Online Analytical Processing (OLAP) is supported.

What programming languages does hive support?

OLAP: Hive is designed for OLAP (Online Analytical Processing). 17. Client application: Hive can support client applications written in PHP, Python, Java, C++ and Ruby.