Hive brings the power of SQL to Hadoop
May 25, 2016

Hive brings the power of SQL to Hadoop

Tom Thomas | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with Apache Hive

I have used Hive at an enterprise company where I interned. It was being used by the IT department to improve analysis of large datasets stored in the company's Hadoop HDFS. It was also being used because of its support for HiveQL which is a SQL like language enabling queries on large datasets. It also reduced the learning curve for handling big data because of HiveQL's similarity to SQL.
  • Supports SQL like queries
  • Various storage types including RCFile, HBase, ORC, etc.
  • Supports indexing for acceleration
  • HiveQL does not have all the features of SQL
  • No support for transactions
  • Reduced learning curve for new trainees and users
  • Support for other client server databases provided improved compatibility of systems
Hive is very well suited for large enterprise businesses that rely on Hadoop for efficient processing of big data in a distributed cluster. HiveQL also brings familiarity of SQL which speeds up the learning process for new users. However, Hive is not an ideal option for a business where data is frequently changing and dynamic.

Using Apache Hive

Hive's support SQL like queries improves its usability since almost every potential user of Hive would have had experience with SQL.
Like to use
Relatively simple
Easy to use
Well integrated
Quick to learn
Feel confident using
Requires technical support
Lots to learn