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  ''This page seems to duplicate ChoosingDatabase, wouldn't it be better to merge shelve and the rest there? -- DanielDittmar [[DateTime(2003-02-11T23:15:22)]]'' <<TableOfContents>>
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[[TableOfContents]] Note: The contents of the ChoosingDatabase page are being merged back into this page.
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= DBMS interfaces =
Things you connect to. [[BR]]
Take a look at
http://www.python.org/topics/database/modules.html and
http://dmoz.org/Computers/Programming/Languages/Python/Modules/Databases_and_Persistence/.
= Generic Database Interfaces and APIs =
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== MySQL ==
 * mysqldb module http://www.mysql.com/downloads/api-python.html
 * SnakeDb (http://www.scriptfoundry.com/modules/snakedb/)
 * 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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== PostgreSQL ==
pypgsql (http://pypgsql.sf.net/)
 Most Python database interfaces adhere to this standard.
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== Oracle ==
 * dcOracle
 * cxOracle
 * 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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== Sybase ==
module developed by Dave Cole http://www.object-craft.com.au/projects/sybase/
== ODBC Support ==
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== MSSQL ==  * ceODBC: http://ceodbc.sourceforge.net
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== BerkeleyDb ==  * pyodbc: http://pyodbc.sourceforge.net
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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

== ADO Support ==

 * adodbapi (http://adodbapi.sourceforge.net/): A Python module that makes it easy to use Microsoft ADO for connecting to databases and other data sources.

= Database Interfaces for Relational Database Systems =

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

== General Purpose Database Systems ==

 * 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]]
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== gadfly ==
Gadfly is a simple relational database system implemented in Python based on the SQL Structured Query Language.
Currently use C-extension module for speed. Pure Python version included.
http://gadfly.sourceforge.net/
== buzhug ==
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== ZODB ==
http://www.zope.org/Wikis/ZODB Zope Object DB
[[http://buzhug.sourceforge.net/|buzhug]] is a pure-Python database engine, using a Pythonic, no-SQL syntax.
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== shelve ==
A [http://www.python.org/doc/current/lib/module-shelve.html ''shelf''] is a persistent, dictionary-like object. The difference with ''dbm'' databases is that the values (not the keys!) in a shelf can be essentially arbitrary Python objects -- anything that the [http://www.python.org/doc/current/lib/module-pickle.html pickle] module can handle. This includes most class instances, recursive data types, and objects containing lots of shared sub-objects. The keys are ordinary strings.
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.
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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.
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= Datafiles interfaces =
Things you open.
== SnakeSQL ==
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== xBase ==
Which stands for .dbf files interface.[[BR]]
.bdf files were produced by several old systems like dBase(II,III,IV), Fox(Base,Pro)
 * xBase (http://linux.techass.com/projects/xdb/) - Python interface in plans
 * http://www.fiby.at/dbfpy.html
 * http://www.sequiter.com/products/Python/
 * http://cbbrowne.com/info/xbase.html
 * http://www.e-bachmann.dk/docs/xbase.htm

== dbm ==
A family of old unix plain hash tables. Has varieties like dbm, ndbm, gdbm, dbmdb185.[[BR]]
See [http://www.python.org/doc/current/lib/module-anydbm.html anydbm],
[http://www.python.org/doc/current/lib/module-dumbdbm.html dumbdbm],
[http://www.python.org/doc/current/lib/module-dbhash.html dbhash],
[http://www.python.org/doc/current/lib/module-bsddb.html bsddb],
[http://www.python.org/doc/current/lib/module-dbm.html dbm],
[http://www.python.org/doc/current/lib/module-gdbm.html gdbm]
in Python Standard Library.

== MetaKit ==
http://www.equi4.com/metakit/python.html

== SQLite ==
Actualy it's a full-fleged SQL server, but embeddable. No external SQL server required. Think of Gadfly, only faster.
http://PySQLite.sf.net

= Special file interface =

 * http://python-dsv.sourceforge.net/ CSV or any separated file (see also PEP:305)
 * ConfigParser.py - Windows .ini format
 * gzip.py
 * zipfile.py
 * tar
 * pdf http://www.pythonware.com/
[[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.

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

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