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Revision 95 as of 2008-12-07 08:55:11
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Comment: corrected name and link to SAP MaxDB interface
Revision 97 as of 2008-12-08 12:34:14
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The contents of this page are being merged into the ChoosingDatabase page. Note: The contents of the ChoosingDatabase page are being merged back into this page.
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= Relational database = = Generic Database Interfaces and APIs =
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Databases based on a relational model, with support for SQL.  * 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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== ODBC ==  Most Python database interfaces adhere to this standard.
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ODBC allows you to use a single library and API to connect to many different databases, including most of those below.  * 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
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 * pyodbc: http://code.google.com/p/pyodbc Open source, mature DB API library == ODBC Support ==
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== MySQL ==
 * mysql-python: http://sourceforge.net/projects/mysql-python
 * ceODBC: http://ceodbc.sourceforge.net
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== PostgreSQL ==  * pyodbc: http://pyodbc.sourceforge.net
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 * psycopg
  * psycopg1: http://initd.org/projects/psycopg1
  * psycopg2: http://initd.org/projects/psycopg2
 * [[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.
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 * pyPgSQL: http://pypgsql.sourceforge.net/  * [[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.
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 * PyGreSQL: http://www.pygresql.org/  * ODBTPAPI: http://benjiyork.com/odbtp.html
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 * PoPy: http://sourceforge.net/projects/popy
  * PoPy and PyGreSQL are [[http://www.zope.org/Members/tm/Full_Announce|merging]]
== ADO Support ==
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 * pg/python: http://python.projects.postgresql.org/
  * pg_proboscis: DB-API 2.0 and GreenTrunk Interfaces http://python.projects.postgresql.org/project/pg_proboscis.html
  * pg_pqueue: PQ 3.0 Protocol elements http://python.projects.postgresql.org/project/pg_pqueue.html
 * adodbapi (http://adodbapi.sourceforge.net/): A Python module that makes it easy to use Microsoft ADO for connecting to databases and other data sources.
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 * pgasync: http://jamwt.com/pgasync/
  * Asynchronous and pure Python. Speed comparable to C bindings. Special support for Twisted.
= Database Interfaces for Relational Database Systems =
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 * bpgsql: http://barryp.org/software/bpgsql/
  * Barebones pure-Python PostgreSQL client
Database systems employing a relational model, with support for SQL.
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 * [[sipPQ]] == General Purpose Database Systems ==
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 * mxODBC: http://www.egenix.com/products/python/mxODBC/
  * Supports the [[http://www.postgresql.org/ftp/odbc/versions/|PostgreSQL ODBC driver]] on both Windows and Unix.
Note that you have to enable the advanced option "Use bytea for lo" in case you want to work with BLOBs.
 * IBM [[DB2]]
 * [[Firebird]] (and Interbase)
 * [[Informix]]
 * [[Ingres]]
 * [[MySQL]]
 * [[Oracle]]
 * [[PostgreSQL]]
 * [[SAP DB]] (also known as "MaxDB")
 * Microsoft [[SQL Server]]
 * [[Sybase]]

(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:

  * GadFly
  * [[SQLite]]
  * [[ThinkSQL]]

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

== Non-Relational Databases ==

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

= Native Python Databases =

== buzhug ==

[[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.

-----

These entries still need to be merged into the resp. sub-pages:
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== Sybase == == Sybase ASE ==
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  * Supports Sybase ASE and Sybase Anywhere.   * Supports Sybase ASE.

== Sybase SQL Anywhere ==

 * sqlanydb: http://dcx.sybase.com/1100en/dbprogramming_en11/pg-python.html
  * Implements with extensions Database API 2.0

 * mxODBC: http://www.egenix.com/products/python/mxODBC/
  * Supports SQL Anywhere.
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== Microsoft SQL Server ==

 * See [[SQL Server]]

= Native Python Databases =

== buzhug ==

[[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.

Note: The contents of the ChoosingDatabase page are being merged back into this page.

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.)

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

Native Python Databases

buzhug

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

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.


These entries still need to be merged into the resp. sub-pages:

Oracle

IBM DB2

  • More info on DB2

Sybase ASE

Sybase SQL Anywhere

MaxDB/SAPDB

Informix

Ingres

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

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