Capabilities of Apache Hive
April 07, 2022
Capabilities of Apache Hive
Score 8 out of 10
Vetted Review
Verified User
Overall Satisfaction with Apache Hive
Main purpose for using Apache Hive was to get the insights from data. Analyzing the data and use it to take informed business decisions. Also the interface is similar to SQL working so it is easy to understand for a new person also.
- It can be used to retrieve data from database like SQL.
- We can partition the data and distribute amongst the clustered machines
- Easily scalable, which gives capability of running analytics at a larger level
- No support for working with Unstructured data.
- ACID properties are not followed like database which creates confusion many times
- Support OLAP environment only, OLTP is not supported
- Similarity to SQL, which doesn't give extra overhead of learning complexity
- Easily scalable for massive analytics to be done
- Distribution and partitioning of data among numerous clustered machines.
- Unable to work in OLTP environment is challenge
- Real time query is not supported currently
- Optimization for query is not proper.
Queries are easy to write and interface is similar to SQL so learning overhead is reduced. Multi user and data type support is provided. Can be easily scaled for very large amount of analytics. It is very flexible in terms of using file formats.
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?
I wasn't involved with the selection/purchase process
Did implementation of Apache Hive go as expected?
Yes
Would you buy Apache Hive again?
Yes