Quick tutorial — CodernityDB Every single part of code block will be full example, so you can copy & paste it to play with it Insert / Save / Store I want to store 100 objects in database Status Autogenerated _id fieldSimple key-value Quick tutorial — CodernityDB
The Search API provides a model for indexing documents that contain structured data. You can search an index, and organize and present search results. The API supports partial text matching on string fields. Documents and indexes are saved in a separate persistent store optimized for search operations. The Search API can index any number of documents. However, an index search can find no more than 10,000 matching documents. Search Overview (Python) - Google App Engine Search Overview (Python) - Google App Engine
Induction/Induction Induction/Induction README.md Induction A Polyglot Database Client for Mac OS X Explore, Query, Visualize Focus on the data, not the database.
djangoappengine - Django App Engine backends (DB, email, etc.) | All Buttons Pressed djangoappengine - Django App Engine backends (DB, email, etc.) | All Buttons Pressed Djangoappengine contains all App Engine backends for Django-nonrel, e.g. the database and email backends. In addition we provide a testapp which contains minimal settings for running Django-nonrel on App Engine. Use it as a starting point if you want to use App Engine as your database for Django-nonrel. We've also published some details in the Django on App Engine blog post. Installation
Neo4j

Bulbflow: a Python Framework for the Graph Era
PyMongo 1.11 Documentation — PyMongo v1.11 documentation PyMongo 1.11 Documentation — PyMongo v1.11 documentation Overview PyMongo is a Python distribution containing tools for working with MongoDB, and is the recommended way to work with MongoDB from Python. This documentation attempts to explain everything you need to know to use PyMongo. Installing / Upgrading Instructions on how to get the distribution. Tutorial
FrontPage - Storm FrontPage - Storm What is Storm? Storm is an object-relational mapper (ORM) for Python developed at Canonical. The project was in development for more than a year for use in Canonical projects such as Launchpad and Landscape before being released as free software on July 9th, 2007. Highlights Design Clean and lightweight API offers a short learning curve and long-term maintainability.
Easy data modeling with PyModels — PyModels v0.18 documentation Easy data modeling with PyModels — PyModels v0.18 documentation PyModels is a lightweight framework for mapping Python classes to schema-less databases. It is not an ORM as it doesn’t map existing schemata to Python objects. Instead, it lets you define schemata on a higher layer built upon a schema-less storage (key/value or document-oriented). You define models as a valuable subset of the whole database and work with only certain parts of existing entities – the parts you need. Topics:
Fast, Easy Database Access with Python
SQLObject SQLObject is a popular Object Relational Manager for providing an object interface to your database, with tables as classes, rows as instances, and columns as attributes. SQLObject includes a Python-object-based query language that makes SQL more abstract, and provides substantial database independence for applications. Examples are good. Examples give a feel for the aesthetic of the API, which matters to me a great deal. SQLObject
SQLAlchemy - The Database Toolkit for Python SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL. It provides a full suite of well known enterprise-level persistence patterns, designed for efficient and high-performing database access, adapted into a simple and Pythonic domain language. SQL databases behave less like object collections the more size and performance start to matter; object collections behave less like tables and rows the more abstraction starts to matter.

SQLAlchemy - The Database Toolkit for Python

Modeling Object-Relational Bridge for python Modeling Object-Relational Bridge for python The Modeling framework intends to fill the gap between the python object world and relational databases. It relies on a model, based on Entity-Relationship Modelling, that describes how the two worlds map to each other. From your design of such a model, the database's schema and corresponding python classes are automatically generated. Thus, once you have designed how your classes should be stored in the RDBMS, you can focus on the real challenges - the logic of your business objects - while remaining in the object-oriented world of those objects and never having to worry about the SQL and RDBMS persistence layer below. You can have a look at some elements of history, which explains why, and how, I did this, and where my ''inspiration'' came from: the Enterprise Object Framework (TM) from Apple, now integrated to their WebObjects application server. See also: the list of the main features.