Databases implemented in Python

There are several databases that have been implemented in Python, including:

SQLite: SQLite is a lightweight, file-based database that is well-suited for small to medium-sized projects. It provides a simple and efficient SQL interface, and it is included as a standard library in many Python distributions.

PostgreSQL: PostgreSQL is a powerful, open-source relational database that is well-suited for large, complex projects. It provides a rich set of features, including transactions, stored procedures, and advanced indexing, and it is widely used in a variety of applications, from web applications to scientific research.

MySQL: MySQL is a widely-used, open-source relational database that is well-suited for small to medium-sized projects. It provides a simple and efficient SQL interface, and it is widely used for a variety of applications, from web applications to data warehousing.

SQLAlchemy: SQLAlchemy is a SQL toolkit and Object-Relational Mapping (ORM) library for Python. It provides a high-level interface for working with databases, and it supports a wide range of databases, including SQLite, PostgreSQL, and MySQL.

Django ORM: Django ORM is an Object-Relational Mapping (ORM) library that is built into the Django web framework. It provides a simple and intuitive interface for working with databases, and it supports a wide range of databases, including SQLite, PostgreSQL, and MySQL.

These are just a few examples of the many databases that have been implemented in Python. The best database for your needs will depend on the specific requirements of your project, as well as your personal preferences and experience.