Open Source Python Database Software
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Python Database Software
View 467 business solutionsBrowse free open source Python Database Software and projects below. Use the toggles on the left to filter open source Python Database Software by OS, license, language, programming language, and project status.
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Gen AI apps are built with MongoDB AtlasMongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
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Firebird
A powerful, cross platform, SQL database system
Firebird RDBMS offers ANSI SQL features & runs on Linux, Windows & several Unix platforms. Features excellent concurrency & performance & powerful stored procedure & trigger language. More information and downloads at https://firebirdsql.org/, issue tracker is https://github.com/FirebirdSQL/firebird/issues -
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LibreOffice
A free and powerful office suite
LibreOffice is a free and powerful office suite, and a successor to OpenOffice. Its clean interface and feature-rich tools help you unleash your creativity and enhance your productivity. LibreOffice is Free and Open Source Software (FOSS) – development is open to new talent and new ideas, and our software is tested and used daily by a large and devoted user community. Your documents will look professional and clean, regardless of their purpose: a letter, a master thesis, a brochure, financial reports, marketing presentations, technical drawings and diagrams. LibreOffice makes your work look great while you focus on the content, thanks to its powerful styles system and structuring tools. LibreOffice is compatible with a wide range of document formats such as Microsoft® Word (.doc, .docx), Excel (.xls, .xlsx), PowerPoint (.ppt, .pptx) and Publisher. But LibreOffice goes much further with its native support for a modern and open standard (OpenDocument Format). -
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Grafana
Leading open-source visualization and observability platform
Grafana OSS is a leading open-source visualization and observability platform that lets you query, visualize, alert on, and explore your data—regardless of where it’s stored. With support for 100+ data source plugins (such as Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, OTel, and more), you can unify metrics, logs, traces, and other observability signals in one place. Grafana OSS empowers you to build dynamic, reusable dashboards with rich visualizations, template variables, interactive filtering, and cross-panel linking. Its Explore mode enables ad-hoc queries and side-by-side comparisons of time ranges, queries, and data sources. Grafana also includes built-in alerting, allowing you to define threshold-based rules and send notifications to external systems (e.g. Slack, PagerDuty, OpsGenie). Backed by a strong community (https://grafana.com/community/) and open governance, Grafana OSS is free to use, modify, and deploy under the AGPL-3.0 license. -
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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. SQLAlchemy 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. An industrial strength ORM, built from the core on the identity map, unit of work, and data mapper patterns. These patterns allow the transparent persistence of objects using a declarative configuration system. Domain models can be constructed and manipulated naturally, and changes are synchronized with the current transaction automatically. A relationally-oriented query system, exposing the full range of SQL's capabilities explicitly, including joins, subqueries, correlation, and most everything else, in terms of the object model. Writing queries with the ORM uses the same techniques of relational composition you use when writing SQL. -
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The MonetDB project has moved to http://www.monetdb.org/.
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MySQL for Python
MySQL database connector for Python programming
MySQLdb is a Python DB API-2.0-compliant interface; see PEP-249 for details. For up-to-date versions of MySQLdb, use the homepage link. Supported versions: * MySQL versions from 3.23 to 5.5; 5.0 or newer recommended. MariaDB should also work. * Python versions 2.4-2.7; Python 3 support coming soon. ZMySQLDA is a Database Adapter for Zope2. -
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A HUD and stats tracker for your poker games written in Python. Supports Holdem, Omaha, Stud, Razz and Draw games.
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imgSeek is a photo collection manager and viewer with content-based search and many other features. The query is expressed either as a rough sketch painted by the user or as another image you supply (or an image in your collection).
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CodeChecker
CodeChecker is an analyzer tooling, defect database
CodeChecker is a static analysis infrastructure built on the LLVM/Clang Static Analyzer toolchain, replacing scan-build in a Linux or macOS (OS X) development environment. Executes Clang-Tidy and Clang Static Analyzer with Cross-Translation Unit analysis, Statistical Analysis (when checkers are available). Creates the JSON compilation database by wiretapping any build process (e.g., CodeChecker log -b "make"). Automatically analyzes GCC cross-compiled projects: detecting GCC or Clang compiler configuration and forming the corresponding clang analyzer invocations. Incremental analysis: Only the changed files and its dependencies need to be reanalyzed. False positive suppression with a possibility to add review comments. Result visualization in command line or in static HTML. Web application for viewing discovered code defects with a streamlined, easy experience (with PostgreSQL, or SQLite backend). -
Grafana: The open and composable observability platformGrafana is the open source analytics & monitoring solution for every database.
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Procrastinate
PostgreSQL-based Task Queue for Python
Procrastinate is a powerful PostgreSQL-based task queue for Python, built to integrate seamlessly with Django and FastAPI. It allows you to schedule and execute background jobs using your existing database infrastructure, avoiding the need for additional queueing systems like Redis. Procrastinate is designed with simplicity, reliability, and observability in mind. -
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SQL Explorer
Easily share data across your company via SQL queries
SQL Explorer aims to make the flow of data between people fast, simple, and confusion-free. It is a Django-based application that you can add to an existing Django site, or use as a standalone business intelligence tool. Quickly write and share SQL queries in a simple, usable SQL editor, preview the results in the browser, share links, download CSV, JSON, or Excel files (and even expose queries as API endpoints, if desired), and keep the information flowing! Comes with support for multiple connections, to many different SQL database types, a schema explorer, query history (e.g. lightweight version control), a basic security model, in-browser pivot tables, and more. SQL Explorer values simplicity, intuitive use, unobtrusiveness, stability, and the principle of least surprise. SQL Explorer is inspired by any number of great query and reporting tools out there. -
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SuperDuperDB
Integrate, train and manage any AI models and APIs with your database
Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. Just using Python. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. SuperDuperDB enables vector search in your existing database. Integrate and combine models from Sklearn, PyTorch, HuggingFace with AI APIs such as OpenAI to build even the most complex AI applications and workflows. Train models on your data in your datastore simply by querying without additional ingestion and pre-processing. -
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WhatsApp Chat Exporter
A cross-platform tool for parsing WhatsApp chat databases
WhatsApp-Chat-Exporter is a customizable tool for parsing WhatsApp databases from Android and iOS devices. It extracts chat histories and exports them in HTML and JSON formats, supporting various encryption standards. -
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mysqlclient
MySQL/MariaDB connector for Python
Summary: mysqlclient is a MySQL/MariaDB connector for Python, providing a convenient interface for database interactions. -
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SQLObject
SQLObject is a Python ORM.
SQLObject is an object-relational mapper for Python. It supports MySQL, PostgreSQL, SQLite, Firebird, MaxDB/SapDB, MS SQL and Sybase. It supports Python versions back to 2.7. -
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Finance Database
This is a database of 300.000+ symbols containing Equities, ETFs, etc.
As a private investor, the sheer amount of information that can be found on the internet is rather daunting. Trying to understand what type of companies or ETFs are available is incredibly challenging with there being millions of companies and derivatives available on the market. Sure, the most traded companies and ETFs can quickly be found simply because they are known to the public (for example, Microsoft, Tesla, S&P500 ETF or an All-World ETF). However, what else is out there is often unknown. This database tries to solve that. It features 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets. It, therefore, allows you to obtain a broad overview of sectors, industries, types of investments and much more. The aim of this database is explicitly not to provide up-to-date fundamentals or stock data as those can be obtained with ease (with the help of this database) by using yfinance, FundamentalAnalysis or ThePassiveInvestor. -
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Full Stack FastAPI and PostgreSQL
Full stack, modern web application generator
Generate a backend and frontend stack using Python, including interactive API documentation. Production ready Python web server using Uvicorn and Gunicorn. Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic). Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs. Minimize code duplication. Multiple features from each parameter declaration. Get production-ready code. With automatic interactive documentation. Many other features including automatic validation, serialization, interactive documentation, authentication with OAuth2 JWT tokens, etc. Celery worker that can import and use models and code from the rest of the backend selectively. REST backend tests based on Pytest, integrated with Docker, so you can test the full API interaction, independent on the database. As it runs in Docker, it can build a new data store from scratch each time. -
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MongoEngine
A Python Object-Document-Mapper for working with MongoDB
MongoEngine is a Python Object-Document Mapper for working with MongoDB. -
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SpeechRecognition
Speech recognition module for Python
Library for performing speech recognition, with support for several engines and APIs, online and offline. Recognize speech input from the microphone, transcribe an audio file, save audio data to an audio file. Show extended recognition results, calibrate the recognizer energy threshold for ambient noise levels (see recognizer_instance.energy_threshold for details). Listening to a microphone in the background, various other useful recognizer features. The easiest way to install this is using pip install SpeechRecognition. The first software requirement is Python 2.6, 2.7, or Python 3.3+. This is required to use the library. PyAudio is required if and only if you want to use microphone input (Microphone). PyAudio version 0.2.11+ is required, as earlier versions have known memory management bugs when recording from microphones in certain situations. To hack on this library, first make sure you have all the requirements listed in the "Requirements" section. -
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Barman for PostgreSQL
Backup and Recovery Manager for PostgreSQL
Barman (backup and recovery manager) is an administration tool for disaster recovery of PostgreSQL servers written in Python. It allows to perform remote backups of multiple servers in business critical environments and help DBAs during the recovery phase. Barman's most wanted features include backup catalogs, retention policies, remote recovery, archiving and compression of WAL files and backups. Barman is written and maintained by PostgreSQL professionals 2ndQuadrant. -
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SYDI is a project aimed to help system administrators in getting started with their Network Documentation. It can document Windows Servers, MS SQL Servers, Exchange Organizations and Linux systems.
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ERAlchemy
Entity Relation Diagrams generation tool
ERAlchemy is a tool that generates Entity-Relationship (ER) diagrams from databases or SQLAlchemy models and vice versa. It’s useful for database documentation, reverse engineering, and understanding complex schemas. ERAlchemy can export diagrams in formats like Graphviz and Mermaid, making it easy to include in reports or markdown files. -
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MySQL Export Laravel Migrations
A MySQL Workbench plugin which exports a Model to Laravel 5 Migrations
A MySQL Workbench plugin that allows for exporting a model to Laravel 5 migrations that follow PSR-2 coding standards. When exported, each migration is generated and saved in it's own, properly named, migration file. -
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athenaSQL
SQL builder for AWS Athena, inspired by sparkSQL
athenaSQL is Athena SQL query builder, inspired by sparkSQL. It borrow some sparkSQL’s concept sparkSQL. It was initially designed to eliminate the need for hard-coding SQL queries as strings within Python scripts and as an alternative to any bespoke SQL query templating. However, it offers the flexibility to be used in various ways as needed. -
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Database mapping layer for MongoDB on Python. Includes schema enforcement and some facilities for schema migration.
