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Note: The contents of the ChoosingDatabase page are being merged back into this page. This page lists database interfaces available for Python. It may also help in finding a suitable database engine for you to use in your Python database applications.
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 * The Python standard for database interfaces is the [[http://www.python.org/dev/peps/pep-0249/|Python DB-API (PEP 249)]]
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 Most Python database interfaces adhere to this standard.  * The Python standard for database interfaces is the [[http://www.python.org/dev/peps/pep-0249/|Python DB-API (PEP 249)]] Most Python database interfaces adhere to this standard.
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 * See also DbApiModuleComparison  * See also [[DbApiModuleComparison|DbApiModuleComparison]]
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 * ceODBC: http://ceodbc.sourceforge.net
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 * pyodbc: http://pyodbc.sourceforge.net  * See [[ODBC|ODBC]]
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 * [[http://www.egenix.com/products/python/mxODBC|mxODBC]]: A commercial Python extension that provides ODBC connectivity on Windows, Linux, Mac OS X, FreeBSD and many other Unix platforms.

 * [[http://www.egenix.com/products/python/mxODBCConnect|mxODBC Connect]]: A commercial client-server product that allows connecting Python to ODBC compatible databases running on remote servers without requiring an ODBC driver on the client side.

 * ODBTPAPI: http://benjiyork.com/odbtp.html
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 * adodbapi (http://adodbapi.sourceforge.net/): A Python module that makes it easy to use Microsoft ADO for connecting to databases and other data sources.
 * See [[ADO|ADO]]
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 * IBM [[DB2]]
 * [[Firebird]] (and Interbase)
 * [[Informix]]
 * [[Ingres]]
 * [[
MySQL]]
 * [[Oracle]]
 * [[
PostgreSQL]]
 * [[SAP DB]] (also known as "MaxDB")
 * Microsoft [[SQL Server]]
 * [[Sybase]]
 * IBM [[DB2|DB2]]
 * [[Firebird|Firebird]] (and Interbase)
 * [[Informix|Informix]]
 * [[Ingres|Ingres]]
 * [[MySQL|
MySQL]]
 * [[Oracle|Oracle]]
 * [[PostgreSQL|
PostgreSQL]]
 * [[SAP DB|SAP DB]] (also known as "MaxDB")
 * Microsoft [[SQL Server|SQL Server]]
 * Microsoft [[Microsoft Access|Access]]
 * [[Sybase|Sybase]]
 * [[InterSystems IRIS]]
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(To add new entries, please choose DatabaseTemplate when creating the page.) (To add new entries, please choose [[DatabaseTemplate|DatabaseTemplate]] when creating the page.)

== Data Warehouse Database Systems ==

 * [[Teradata|Teradata]]
 * IBM [[Netezza|Netezza]]

(To add new entries, please choose [[DatabaseTemplate|DatabaseTemplate]] when creating the page.)
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  * GadFly
  * [[SQLite]]
  * [[ThinkSQL]]
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(To add new entries, please choose DatabaseTemplate when creating the page.)  * [[asql|asql]]
 * [[GadFly|GadFly]]
 * [[SQLite|SQLite]]
 * [[ThinkSQL|ThinkSQL]]
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== Non-Relational Databases ==
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  * MetaKit
  * [[ZODB]]
  * [[BerkeleyDB]]
  * [[KirbyBase]]
  * [[Durus]]
  * [[atop]]
  * [[buzhug]]
(To add new entries, please choose [[DatabaseTemplate|DatabaseTemplate]] when creating the page.)


= Non-Relational Databases =


== Record-based Databases ==


Databases working on flat files or fixed records.


 * [[MetaKit|MetaKit]]
 * [[ZODB|ZODB]]
 * [[BerkeleyDB|BerkeleyDB]]
 * [[KirbyBase|KirbyBase]]
 * [[Durus|Durus]]
 * [[atop|atop]]
 * [[buzhug|buzhug]]


(To add new entries, please choose [[DatabaseTemplate|DatabaseTemplate]] when creating the page.)


== XML Databases ==


 * 4Suite server
 * Oracle/Sleepycat DB XML ([[http://jimmyg.org/blog/2008/oracle-db-xml-was-sleepycat.html|howto]])


== Graph Databases ==


 * [[Neo4j|Neo4j]]


(To add new entries, please choose [[DatabaseTemplate|DatabaseTemplate]] when creating the page.)
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== buzhug ==
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[[http://buzhug.sourceforge.net/|buzhug]] is a pure-Python database engine, using a Pythonic, no-SQL syntax.

The data is stored and accessed on disk (it is not an in-memory database). The implementation has been designed to make all operations, and especially selection, as fast as possible with an interpreted language.

A limited benchmark using the same use cases as SQLite's author shows that buzhug is much faster than other pure-Python modules (KirbyBase, gadfly). SQLite, which is implemented in C, is faster, but only less than 3 times on the average.

== SnakeSQL ==

[[http://www.pythonweb.org/projects/snakesql/|SnakeSQL]] is a pure Python SQL database written to remove the dependence of the Python Web Modules on 3rd party drivers for non-Python databases like MySQL but designed to be a useful database in its own right.
 * [[buzhug|buzhug]]
 * [[SnakeSQL|SnakeSQL]]

This page lists database interfaces available for Python. It may also help in finding a suitable database engine for you to use in your Python database applications.

Generic Database Interfaces and APIs

  • The Python standard for database interfaces is the Python DB-API (PEP 249) Most Python database interfaces adhere to this standard.

  • Most databases have ODBC support; see the section below on ODBC modules.
  • Java databases usually support JDBC, and can be used from Jython.
  • See also DbApiModuleComparison

ODBC Support

ADO Support

Database Interfaces for Relational Database Systems

Database systems employing a relational model, with support for SQL.

General Purpose Database Systems

(To add new entries, please choose DatabaseTemplate when creating the page.)

Data Warehouse Database Systems

(To add new entries, please choose DatabaseTemplate when creating the page.)

Database Systems for Embedding Into Applications

The following database systems are more oriented towards embedded applications:

(To add new entries, please choose DatabaseTemplate when creating the page.)

Non-Relational Databases

Record-based Databases

Databases working on flat files or fixed records.

(To add new entries, please choose DatabaseTemplate when creating the page.)

XML Databases

  • 4Suite server
  • Oracle/Sleepycat DB XML (howto)

Graph Databases

(To add new entries, please choose DatabaseTemplate when creating the page.)

Native Python Databases

DatabaseInterfaces (last edited 2020-12-09 09:29:13 by MarcAndreLemburg)

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