Is Hive Good At Everything? - Big Data In Real World

Is Hive Good At Everything?

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Is Hive Good At Everything?

Hive is an awesome tool, which takes in SQL like queries and translate them in to MapReduce. Hive is very helpful in working with complex data and helps in visualizing the data in row columnar fashion (which is liberating).

Just because Hive can take in SQL like queries and execute them like a database system does, can it do everything a database can do?

The answer is NO.

Hive has a lot of limitations when compared to a database system like MySQL or Oracle. Here are some of the limitations in Hive when compared to a traditional database system.

  1. Hive can not do pointed updates or deletes. The closest to delete you get is by dropping partitions. Why? Because behind the scenes, Hive works against files in HDFS.
  2. Hive does not support triggers
  3. Transactions – Very high level support and it is recently added. Reference
  4. Indexes – Rudimentary support. Reference
  5. Views – Read-only views are allowed. Materialized views are not supported.
  6. Speed – Hive relies on MapReduce and Hadoop for execution, which works very well with big datasets but not great for split second results.
Big Data In Real World
Big Data In Real World
We are a group of Big Data engineers who are passionate about Big Data and related Big Data technologies. We have designed, developed, deployed and maintained Big Data applications ranging from batch to real time streaming big data platforms. We have seen a wide range of real world big data problems, implemented some innovative and complex (or simple, depending on how you look at it) solutions.

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Is Hive Good At Everything?
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