Help your dev team !
April 12, 2022

Help your dev team !

Anonymous | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with Apache Hive

We build our data lake and perform queries on large amounts of data. We group data from multiple sources into a common structure, making it easy for our developers to perform complex queries without leaving the simple framework provided by SQL. Although the deployment is not easy, once we have the infrastructure, the work is greatly simplified.
  • Simplify query to devs
  • Organize data
  • Batch process
  • Deploy
  • Maintenance
  • Support
  • Batch
  • Easy of use to devs
  • Community support
  • Reduce time to market
  • Improve client satisfaction
  • Saves money :)
Community support and ease of use -not deployment.

It enables querying and analyzing large amounts of data stored in HDFS, on the petabyte scale. It has a query language called HQL that transforms SQL queries into MapReduce jobs that run on Hadoop, and it is wonderful for the devs team that love it.

Do you think Apache Hive delivers good value for the price?


Are you happy with Apache Hive's feature set?


Did Apache Hive live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Apache Hive go as expected?


Would you buy Apache Hive again?


It is great for laboratory environments and to start working with unstructured data about which we are not very clear about how we want to treat it. It also allows queries to be improved very quickly by allowing developers to work with SQL instead of map-reduce. As an improvement, in productive environments, troubleshooting is complicated and requires expert personnel.