Open-source Amazon DocumentDB alternatives

SurrealDB is a Rust-based multi-model database that brings several data models into one engine: key-value, document, graph, relational, time-series and geospatial data. Search and retrieval options include full-text, vector and hybrid, and it adds real-time and event-driven capabilities, queried through its SQL-like language, SurrealQL.

Because it supports end-user authentication, SurrealDB can also act as a backend-as-a-service, reducing the amount of server-side code an app needs. It ships as a single Rust binary that can run embedded inside an application, in the browser via WebAssembly, at the edge, as a self-hosted single node, or as a distributed cluster in the cloud. Typical workloads include data-intensive systems that need several data types, storage for AI agents, knowledge graphs, live applications such as recommenders and fraud detection, and embedded or edge deployments.

The repository license is listed as 'Other' on GitHub, so confirm the terms before commercial use. SurrealDB also offers cloud-hosted database service, and topics tag it as a serverless, realtime database for the web.

This repository holds the source of MongoDB, the document-oriented NoSQL database. It is written in C++ and contains the main server components: mongod, the database server, and mongos, the router used for sharded clusters. MongoDB stores flexible JSON-like documents rather than rows in fixed tables.

Most users install prebuilt packages rather than building from source. The README points to the community server download page, the mongodb-community-server Docker image and Homebrew taps, and also covers the MongoDB Shell, mongosh, and MongoDB Compass, a graphical client that can be installed with a packaged script. Client drivers exist for most programming languages, and RPM and Debian packages are produced by the build scripts. Documentation and a developer center help with learning.

The repository's license is listed as 'Other' on GitHub, so read the current license terms before building services on it. MongoDB can be run on your own infrastructure, and MongoDB Inc. also operates a managed cloud service. It is widely used as a general-purpose database for applications with evolving schemas.

ArangoDB is a multi-model database that stores documents, graphs and key-value data in a single engine. Instead of running separate systems for each data model, applications query connected data through one SQL-like language, with JavaScript extensions available for custom logic.

Every node in a graph is a JSON document, so existing document data can be imported and relationships can be queried across multiple levels of joins. ArangoSearch, an integrated search engine, adds text search and ranking. For scale and resilience the database can shard data horizontally across machines and replicate it to cluster nodes with automatic failover.

ArangoDB can be installed from a download or started in Docker, and runs on-premises or in any cloud. The Arango Managed Platform (AMP) creates deployments on major cloud providers and can be tried for free. A free Community Edition and a commercial Enterprise Edition without a dataset size limit are offered; the repository lists its license simply as Other, so check the terms before production use.

Apache CouchDB is a database that stores JSON documents and is reached through an HTTP/JSON API. Its headline feature is multi-primary sync: the Couch Replication Protocol lets data flow between server clusters, mobile phones and web browsers, which supports offline-first applications that reconcile changes when connectivity returns.

It can run as a single-node database behind an application server or as a cluster, stores binary data alongside JSON, and offers a developer-friendly query language with optional MapReduce views. The protocol is implemented by a variety of projects and products across computing environments. CouchDB is written in Erlang, known for reliability, and the homepage presents the design as built for dependable operation.

Apache CouchDB is licensed under Apache-2.0 and runs on your own servers or with any cloud provider. Documentation, a technical overview and download packages are on the project site. It suits teams building apps that must keep working offline and sync later, or that want a simple, HTTP-native document store.

RavenDB is a NoSQL document database that is fully ACID and secure by default. Its makers, frustrated with the state of the database industry, aim to combine strong performance with ease of use so developers can concentrate on their application instead of managing data infrastructure. It is built on .NET.

Repository topics list full-text search, indexing, sharding, spatial queries, time series, vector search and IoT use, and the README links to documentation, articles, a book and a try-from-your-browser option. It describes itself as completely open source under AGPLv3 and mentions a free developer license, while GitHub reports the license as 'Other', so confirm the terms for production use.

RavenDB can be run on your own servers or consumed as a managed cloud service from the vendor, which also sells commercial licenses. It suits .NET teams that want a document store with transactions, indexing and search built in.

FerretDB is an open-source alternative to MongoDB. It works as a proxy that accepts queries in the MongoDB 5.0+ wire protocol, converts them to SQL and stores the data in PostgreSQL with the DocumentDB extension, so existing MongoDB drivers and popular tools can usually talk to it without code changes.

The project was started because MongoDB moved to the SSPL licence, which made it unsuitable for many open-source and early-stage commercial projects. FerretDB targets the common case of developers who want an easy-to-use document database without needing MongoDB's most advanced features, and in many cases it can act as a drop-in replacement. A public roadmap lists known differences and supported commands.

FerretDB is written in Go and released under the Apache-2.0 licence. A Docker quickstart bundles the proxy, PostgreSQL with DocumentDB and the MongoDB Shell for experiments, while separate installation guides cover production setups that do not lose data on shutdown. You run it on your own infrastructure alongside PostgreSQL.