What are the characteristics and contrasts between Hive and HBase?

Created: Oct 12, 2019 03:23:56Latest reply: Oct 12, 2019 05:32:16 412 4 3 1
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I'm interested in finding out how the recently-released Hive compares to HBase in terms of performance. The SQL-like interface used by Hive is very much preferable to the HBase API we have implemented.What are the characteristics of Hive and Hbase?


Thanks in advance.

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Featured Answers
songminwang
Admin Created Oct 12, 2019 03:27:47 Helpful(3) Helpful(3)

Hive:

Pros:

  1. Hive is a data warehouse infrastructure built on top of Hadoop.
  2. It allows for querying data stored on HDFS for analysis via HQL, an SQL-like language, which will be converted into series of Map Reduce Jobs
  3. It only runs batch processes on Hadoop.
  4. it’s JDBC compliant, it also integrates with existing SQL based tools
  5. Hive supports partitions
  6. It supports analytical querying of data collected over a period of time

Cons:

  1. It does not currently support update statements
  2. It should be provided with a predefined schema to map files and directories into columns

HBase:

Pros:

  1. A scalable, distributed database that supports structured data storage for large tables
  2. It provides random, real time read/write access to your Big Data. HBase operations run in real-time on its database rather than MapReduce jobs
  3. it supports partitions to tables, and tables are further split into column families
  4. Scales horizontally with huge amount of data by using Hadoop
  5. Provides key based access to data when storing or retrieving. It supports add or update rows.
  6. Supports versoning of data.

Cons:

  1. HBase queries are written in a custom language that needs to be learned
  2. HBase isn’t fully ACID compliant
  3. It can't be used with complicated access patterns (such as joins)
  4. It is also not a complete substitute for HDFS when doing large batch MapReduce
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All Answers
songminwang
songminwang Admin Created Oct 12, 2019 03:27:47 Helpful(3) Helpful(3)

Hive:

Pros:

  1. Hive is a data warehouse infrastructure built on top of Hadoop.
  2. It allows for querying data stored on HDFS for analysis via HQL, an SQL-like language, which will be converted into series of Map Reduce Jobs
  3. It only runs batch processes on Hadoop.
  4. it’s JDBC compliant, it also integrates with existing SQL based tools
  5. Hive supports partitions
  6. It supports analytical querying of data collected over a period of time

Cons:

  1. It does not currently support update statements
  2. It should be provided with a predefined schema to map files and directories into columns

HBase:

Pros:

  1. A scalable, distributed database that supports structured data storage for large tables
  2. It provides random, real time read/write access to your Big Data. HBase operations run in real-time on its database rather than MapReduce jobs
  3. it supports partitions to tables, and tables are further split into column families
  4. Scales horizontally with huge amount of data by using Hadoop
  5. Provides key based access to data when storing or retrieving. It supports add or update rows.
  6. Supports versoning of data.

Cons:

  1. HBase queries are written in a custom language that needs to be learned
  2. HBase isn’t fully ACID compliant
  3. It can't be used with complicated access patterns (such as joins)
  4. It is also not a complete substitute for HDFS when doing large batch MapReduce
  • x
  • convention:

songminwang
songminwang Admin Created Oct 12, 2019 03:30:55 Helpful(2) Helpful(2)

Hive is an analytics tool. Just like pig, it was designed for ad hoc batch processing of potentially enourmous amounts of data by leveraging map reduce. Think terrabytes. Imagine trying to do that in a relational database...

HBase is a column based key value store based on BigTable. You can't do queries per se, though you can run map reduce jobs over HBase. It's primary use case is fetching rows by key, or scanning ranges of rows. A major feature is being able to have data locality when scanning across ranges of row keys for a 'family' of columns.

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liqiang185
liqiang185 Created Oct 12, 2019 03:35:26
It's very useful to me.  
wissal
wissal MVE Created Oct 12, 2019 05:32:16 Helpful(1) Helpful(1)

Hello,

Hive vs. HBase - Difference between Hive and HBase

  • Hive is query engine that whereas HBase is a data storage particularly for unstructured data.
  • Apache Hive is mainly used for batch processing i.e. OLAP but HBase is extensively used for transactional processing wherein the response time of the query is not highly interactive i.e. OLTP.
  • Unlike Hive, operations in HBase are run in real-time on the database instead of transforming into mapreduce jobs.
  • HBase is to real-time querying and Hive is to analytical queries.
Thanks
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