DBMS > HBase vs. Hive vs. Impala

System Properties Comparison HBase vs. Hive vs. Impala

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Analytic DBMS for Hadoop

Primary database model

Wide column store

Relational DBMS

Secondary database models

Document store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	57.54
Rank	#18	Overall
	#2	Wide column stores

Score	80.87
Rank	#14	Overall
	#9	Relational DBMS

Score	14.86
Rank	#37	Overall
	#23	Relational DBMS

Website

hbase.apache.org

hive.apache.org

www.cloudera.com/products/open-source/apache-hadoop/impala.html

Technical documentation

hbase.apache.org

cwiki.apache.org/confluence/display/Hive/Home

www.cloudera.com/documentation/enterprise/latest/topics/impala.html

Developer

Apache Software Foundation info

Apache top-level project, originally developed by Powerset

Apache Software Foundation info

initially developed by Facebook

Cloudera

Initial release

2008

2012

2013

Current release

2.2.0, June 2019

2.3.5, May 2019

3.2.0, March 2019

License

Commercial or Open Source

Open Source info

Apache version 2

Open Source info

Apache Version 2

Open Source info

Apache Version 2

Cloud-based only info

Only available as a cloud service

DBaaS offerings (sponsored links) info

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Linux
Unix
Windows info

using Cygwin

All OS with a Java VM

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support info

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

Java API
RESTful HTTP API
Thrift

JDBC
ODBC
Thrift

JDBC
ODBC

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

C++
Java
PHP
Python

All languages supporting JDBC/ODBC

Server-side scripts info

Stored procedures

yes

Coprocessors in Java

yes

user defined functions and integration of map-reduce

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods info

Methods for storing different data on different nodes

Sharding

Replication methods info

Methods for redundantly storing data on multiple nodes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

query execution via MapReduce

Consistency concepts info

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys info

Referential integrity

Transaction concepts info

Support to ensure data integrity after non-atomic manipulations of data

Concurrency info

Support for concurrent manipulation of data

yes

Durability info

Support for making data persistent

yes

In-memory capabilities info

Is there an option to define some or all structures to be held in-memory only.

User concepts info

Access control

Access Control Lists (ACL) info

Implementation based on Hadoop and ZooKeeper

Access rights for users, groups and roles

Access rights for users, groups and roles info

based on Apache Sentry and Kerberos

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