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Apache Hive: SQL, open-source querying tool
September 18, 2020

Apache Hive: SQL, open-source querying tool

Anonymous | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User

Overall Satisfaction with Apache Hive

Our company primarily uses Apache Hive to manage our data warehouse by being able to query multiple databases. We partition our tables as well as monitor query performance on very custom data queries by using this hive. Hive is only used by our data analysts and an overseas data warehouse team with only a few shared licenses existing on our virtual machines.
  • Monitor query performance
  • Manage tables in the data warehouse
  • Uses standard SQL
  • UI is quite dated and not intuitive
  • Open-source, so does not have consistent updates or support
  • Not the most optimal for ETL processes
  • No licensing costs
  • Little training needed for most users
Open-source software with little incentive to innovate or have consistent support to push out updates and changes to the platform
It uses standard SQL, which most architects and developers are quite familiar with writing. The user interface and general intuitiveness of navigation are very dated and will require some searching for documentation before being able to find what certain functions are able to do. Works well but is still quite slow compared to similar products such as Impala.

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

Yes

Are you happy with Apache Hive's feature set?

Yes

Did Apache Hive live up to sales and marketing promises?

No

Did implementation of Apache Hive go as expected?

No

Would you buy Apache Hive again?

Yes

Apache Hive is well suited for organizations looking for an initial tool to begin their process of managing their data warehouse as it is open-source and relatively easy to set up. This works well with some legacy systems and many consoles support this. While Hive used to be quite revolutionary, it has fallen behind many other tools that are more performant or specialized for managing DBs, writing queries, and partitioning tables.