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Basics of HBase

Last updated on Jun 05,2023 14.1K Views

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HBase is an open source, non-relational, distributed database modelled after Google’s BigTable and is written in Java. It is developed by Apache Software Foundation and is a part of Apache Hadoop project. HBase runs on top of HDFS (Hadoop Distributed Filesystem), providing BigTable-like capabilities for Hadoop.

HBase is a key/ value store. HBase is specifically Sparse, Distributed, Multi-dimensional, sorted Maps and consistent.

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HBase can be used in the following scenarios:

  • Huge Data
  • Fast Random Access
  • Structured Data
  • Variable Schema
  • Need of Compression
  • Need of Sharding

NoSQL Landscape:

The NoSQL databases can be classified as follows:

  • Key-Value Stores – Dynamo (Amazon), Voldemort (LinkedIn), Citrusleaf, Membasae, Riak, Tokyo Cabinet, etc.
  • Big Table Clones – BigTable(Google), Cassandra, HBase, Hypertable, etc.
  • Document Database – CouchOne, MongoDB, Terrastore, OrientDB, etc.
  • Graph Databases – FlockDB (Twitter), AllegroGraph, DEX, InfoGRid, Neo4J, Sones, etc.

    You can get a better understanding with the
    Azure Data Engineering Certification.

Features of HBase:

Features-of-HBase-Basics-of-HBase-EdurekaHistory of HBase:

Basics of HBase

Basics of HBase:

The following keywords are required to gain an understanding of the subjects that forms the core foundation of HBase:

 
  • Rowkey
  • Column Family
  • Column
  • Timestamp

An HBase table contains column families, which are the logical and physical grouping of columns. Column families contain columns with time stamped versions. Columns only exist when they are inserted. All column associates of the same column family have the same column family prefix. Each column value is identified by a key. The row key is the implicit primary key. The Rows are sorted by the row key.

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Related Posts:

Big Data and Hadoop Training

 

Overview of HBase Storage Architecture

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Basics of HBase

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