DBMS > Drizzle vs. IBM Db2 warehouse vs. MariaDB vs. Sphinx vs. Teradata

System Properties Comparison Drizzle vs. IBM Db2 warehouse vs. MariaDB vs. Sphinx vs. Teradata

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.

Cloud-based data warehousing service

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

Open source search engine for searching in data from different sources, e.g. relational databases

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.34
Rank	#166	Overall
	#76	Relational DBMS

Score	93.81
Rank	#13	Overall
	#9	Relational DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Score	47.84
Rank	#21	Overall
	#15	Relational DBMS

Website

www.ibm.com/products/db2/warehouse

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

sphinxsearch.com

www.teradata.com

Technical documentation

mariadb.com/kb/en/library

sphinxsearch.com/docs

docs.teradata.com

Developer

Drizzle project, originally started by Brian Aker

IBM

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Sphinx Technologies Inc.

Teradata

Initial release

2008

2014

2009

Fork of MySQL, which was first released in 1995

2001

1984

Current release

7.2.4, September 2012

11.3.2, February 2024

3.5.1, February 2023

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

GPL version 2, commercial licence available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C and C++

C++

Server operating systems

FreeBSD
Linux
OS X

hosted

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

hosted
Linux

Data scheme

yes

Dynamic columns are supported

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.

Import/export of XML data possible

yes

Secondary indexes

yes

full-text index on all search fields

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

with proprietary extensions

yes

with proprietary extensions

SQL-like query language (SphinxQL)

yes

SQL 2016 + extensions

APIs and other access methods

JDBC

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C
C++
Java
PHP

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Ada
C
C#
C++
D
Eiffel
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

PL/SQL, SQL PL

yes

PL/SQL compatibility added with version 10.3

yes

UDFs, stored procedures, table functions in parallel

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

several options for horizontal partitioning and Sharding

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

not for in-memory storage engine

yes

The original contents of fields are not stored in the Sphinx index.

yes

In-memory capabilities

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

yes

with MEMORY storage engine

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Web, SaaS and Cloud operational applications that require high availability, scalability...
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Key customers

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Market metrics

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Licensing and pricing models

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