DBMS > Drizzle vs. Hive vs. Infobright vs. Percona Server for MySQL

System Properties Comparison Drizzle vs. Hive vs. Infobright vs. Percona Server for MySQL

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

Primary database model

Relational DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	2.03
Rank	#122	Overall
	#57	Relational DBMS

Website

hive.apache.org

ignitetech.com/softwarelibrary/infobrightdb

www.percona.com/software/mysql-database/percona-server

Technical documentation

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

www.percona.com/downloads/Percona-Server-LATEST

Developer

Drizzle project, originally started by Brian Aker

Apache Software Foundation

initially developed by Facebook

Ignite Technologies Inc.; formerly InfoBright Inc.

Percona

Initial release

2008

2012

2005

2008

Current release

7.2.4, September 2012

3.1.3, April 2022

8.0.36-28, 2024

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

GPL version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C and C++

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

Linux
Windows

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

XML support

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

yes

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC

Supported programming languages

C
C++
Java
PHP

C++
Java
PHP
Python

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

Source-replica replication

Multi-source replication
Source-replica replication
XtraDB Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Users with fine-grained authorization concept

no user groups or roles

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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