FerretDB

Overview

FerretDB allows you to use MongoDB drivers seamlessly with PostgreSQL as the database backend. Use all tools, drivers, UIs, and the same query language and stay open-source.

Key Features

  • MongoDB-Compatible API:

FerretDB offers a MongoDB-compatible API, allowing applications designed for MongoDB to interact with FerretDB without modification. This compatibility makes it easy to use FerretDB as a drop-in replacement for MongoDB.

  • Open-Source and Fully Transparent:

FerretDB is open-source, providing full transparency into its source code and development. This openness allows users to review, modify, and contribute to the project, fostering community involvement and trust.

  • SQL-Based Storage Engine:

Utilizes a SQL-based storage engine to manage data. By converting MongoDB queries into SQL queries, FerretDB can leverage mature SQL database technologies for storage and query execution.

  • Schema-Free Data Model:

Supports a schema-free data model, similar to MongoDB. This flexibility allows users to store and manage data without enforcing a rigid schema, accommodating diverse data types and structures.

  • Advanced Query Support:

Provides advanced query capabilities, including support for complex queries and indexing. This feature enables efficient data retrieval and manipulation, supporting a wide range of application requirements.

  • Scalability and Performance:

Designed to offer scalability and high performance. FerretDB can handle large volumes of data and high query loads, making it suitable for use in production environments with demanding performance needs.

Use Cases

  • MongoDB Replacement:

Ideal for applications that require a MongoDB-compatible database but seek the benefits of an open-source, SQL-based storage solution. FerretDB provides a seamless transition for MongoDB users.

  • Open-Source Database Projects:

Suitable for developers and organizations that prefer open-source solutions. FerretDB’s open nature allows for extensive customization and community contributions.

  • SQL-Based Storage Needs:

Useful for scenarios where SQL-based storage and querying are preferred. FerretDB leverages SQL technologies to manage data, offering an alternative to traditional NoSQL databases.

  • Schema-Free Data Management:

Supports applications that need flexible, schema-free data storage. Ideal for use cases where data structure is not fixed and may evolve over time.

  • High-Performance Applications:

Designed for applications with high-performance requirements. FerretDB’s scalability and advanced query capabilities make it suitable for handling large datasets and high query volumes.

FerretDB Docs