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Easy access to data in Hadoop
Updated February 14, 2017

Easy access to data in Hadoop

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

Overall Satisfaction with Apache Hive

Apache Hive is primarily used by data analysts and data engineers at our company. We store most of our data in Hadoop and Apache Hive allows us to access the data faster than by writing MapReduce jobs.
  • Faster than writing MapReduce or scalding jobs to access data in Hadoop.
  • Syntax is essentially the same as that of SQL, making the barriers for entry to start using data low.
  • Apache Hive can be quite slow and is not suitable for interactive querying. Simple queries will take many minutes and more complex queries can take a very long time to finish running.
  • Faster turnaround time for data asks that require access to data stored in Hadoop
  • Less overhead in training to learn MapReduce/Scala when trying to access data in Hadoop
Presto is slightly less reliable but much faster for interactive querying. These tools would not be replacements for each other, but rather complements.
Apache Hive is suitable for allowing easy access to data stored in Hadoop via a familiar SQL syntax. It is more suitable for one-off data pulls and less suitable for interactive querying due to its speed. For a better interactive querying experience, a solution like Presto would be more suitable.