Open Source Rust Database Software - Page 2
Sort By:
Rust Database Software
View 474 business solutionsBrowse free open source Rust Database Software and projects below. Use the toggles on the left to filter open source Rust Database Software by OS, license, language, programming language, and project status.
-
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
1
SpacetimeDB
Multiplayer at the speed of light
SpacetimeDB is a high-performance, distributed database optimized for real-time multiplayer applications. It offers low-latency data synchronization across clients, ensuring a seamless and responsive user experience. With built-in conflict resolution and support for complex data types, SpacetimeDB simplifies the development of interactive, collaborative applications. -
2
Stoolap
A Modern Embedded SQL Database written in Rust
Stoolap is a lightweight, self-hosted analysis and visualization tool designed to help developers and operations teams explore log data, metrics, and debugging information from distributed systems or local applications. Instead of relying on heavy commercial observability platforms, stoolap provides a fast, focused interface where users can filter, query, and visualize time-series data, logs, traces, and error metrics in a cohesive environment. Its intuitive query builder lets users craft powerful filters and aggregations without complex configurations, making it easier to diagnose performance bottlenecks or uncover unusual events during testing and production. Stoolap supports dashboards, alert triggering, and exports so teams can embed visualizations in reports or monitor critical thresholds in real time. -
3
Supabase Wrappers
Postgres Foreign Data Wrapper development framework in Rust
Supabase Wrappers is a collection of PostgreSQL extensions (written in Rust) that allow Postgres to interact with external systems like APIs, files, and other databases. It uses Foreign Data Wrappers (FDWs) to treat external resources as if they were native SQL tables, enabling seamless integration with external services directly from SQL queries. -
4
TensorBase
TensorBase is a new big data warehousing with modern efforts
TensorBase hopes the open source not become a copy game. TensorBase has a clear-cut opposition to fork communities, repeat wheels, or hack traffic for so-called reputations (like Github stars). After thoughts, we decided to temporarily leave the general data warehousing field. For people who want to learn how a database system can be built up, or how to apply modern Rust to the high-performance field, or embed a lightweight data analysis system into your own big one. You can still try, ask or contribute to TensorBase. The committers are still around the community. We will help you in all kinds of interesting things pursued in the project by us and maybe you. We still maintain the project to look forward to meeting more database geniuses in this world, although no new feature will be added in the near future. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
5
Trailbase
A blazingly fast, open-source application server with type-safe APIs
A blazingly fast, open-source application server with type-safe APIs, built-in JS/ES6/TS Runtime, Auth, and Admin UI built on Rust, SQLite & V8. Simplify with fewer moving parts: an easy-to-self-host, single-file, extensible backend for your mobile, web, or desktop application. Sub-millisecond latencies eliminate the need for dedicated caches, no more stale or inconsistent data. -
6
Turso Database
Turso is an in-process SQL database, compatible with SQLite
Turso is an in-process SQL database written in Rust and designed to stay compatible with SQLite. It supports SQLite’s SQL dialect, file formats, and C API while adding newer database capabilities. The project is currently in beta, so it is best used with care and proper backups for production data. Turso includes support for concurrent writes through MVCC, change data capture, and faster schema management. It offers bindings and integrations across languages such as Rust, JavaScript, Go, Python, Java, .NET, and WebAssembly. The database also includes vector support, asynchronous Linux I/O with io_uring, and a built-in MCP server that lets AI assistants inspect and modify databases through structured tools. -
7
VectorChord
Scalable, fast, and disk-friendly vector search in Postgres
VectorChord is an open-source vector database built for local and edge deployment. It supports efficient vector indexing and retrieval using ANN (approximate nearest neighbor) algorithms and is optimized for integration with LLM and AI applications. VectorChord is lightweight and can be embedded in a variety of environments for fast semantic search. -
8
WebApp.rs
A web application completely written in Rust
A web application completely written in Rust. Target of this project is to write a complete web application including the backend and front within Rust. The app consists of a frontend and a backend. For getting started with hacking, the backend can be tested via make run-backend, whereas the frontend can be tested with make run-frontend. You can adapt the application configuration within Config.toml if needed. make deploy uses podman to start a PostgreSQL container and the Rust backend container. If you wish to use docker instead of podman, set CONTAINER_RUNTIME=docker in the top of Makefile. Edit Config.toml if needed to set the backend url and PostgreSQL credentials. The login screen will accept any username and password that are equal, such as me (username) and me (password). There is currently no further user authentication yet, but nonmatching combination will result in an authentication failure. -
9
ZomboDB
Making Postgres and Elasticsearch work together like it's 2023
ZomboDB is a PostgreSQL extension that integrates Elasticsearch directly into Postgres, allowing for powerful full-text search and analytics capabilities. It manages Elasticsearch indices transparently, ensuring transactional consistency and enabling complex queries through SQL. -
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
-
10
falkordb
A super fast Graph Database
A super fast Graph Database uses GraphBLAS under the hood for its sparse adjacency matrix graph representation. Our goal is to provide the best Knowledge Graph for LLM (GraphRAG). -
11
gobang
A cross-platform TUI database management tool written in Rust
A cross-platform TUI database management tool written in Rust. Cross-platform support (macOS, Windows, Linux). Multiple Database support (MySQL, PostgreSQL, SQLite). Intuitive keyboard-only control. gobang means a Japanese game played on goban, a go board. The appearance of goban looks like table structure. If you’re using Homebrew or Linuxbrew, install the gobang formula. If you want to add connections, you need to edit your config file. -
12
pg_analytics
DuckDB-powered analytics for Postgres
pg_analytics (formerly named pg_lakehouse) puts DuckDB inside Postgres. With pg_analytics installed, Postgres can query foreign object stores like AWS S3 and table formats like Iceberg or Delta Lake. Queries are pushed down to DuckDB, a high-performance analytical query engine. By transforming Postgres into a performant search and analytics engine, ParadeDB frees your team from the pain of scaling and syncing Elasticsearch. -
13
pg_mooncake
Real-time analytics on Postgres tables
pg_mooncake is a PostgreSQL extension that brings observability and performance insights to your database by exposing low-level metrics and analytics. It provides developers with enhanced visibility into query execution, memory usage, and system behavior. Ideal for fine-tuning Postgres performance, pg_mooncake is designed for those who need actionable insights without external tools. -
14
pgcat
PostgreSQL pooler with sharding, load balancing and failover support
PgCat is a high-performance PostgreSQL connection pooler and load balancer built for modern, distributed systems. Written in Rust, PgCat is designed to efficiently manage database connections across multiple shards and replicas while supporting features like automatic failover, query-based routing, and observability. It works with both single-node and multi-tenant Postgres setups, making it ideal for cloud-native applications that require scale and reliability. -
15
rust-rocksdb
Rust wrapper for rocksdb
Binding is statically linked with a specific version of RocksDB. If you want to build it yourself, make sure you've also cloned the RocksDB and compression submodules. By default, support for the Snappy, LZ4, Zstd, Zlib, and Bzip2 compression is enabled through crate features. If support for all of these compression algorithms is not needed, default features can be disabled and specific compression algorithms can be enabled. The underlying RocksDB does allow column families to be created and dropped from multiple threads concurrently. But this crate doesn't allow it by default for compatibility. If you need to modify column families concurrently, enable crate feature called multi-threaded-cf, which makes this binding's data structures to use RwLock by default. -
16
seladb/pickledb-rs
PickleDB-rs is a lightweight and simple key-value store
PickleDB-RS is a lightweight, fast, and key-value store written in Rust. Inspired by the Python PickleDB, it provides a simple, NoSQL database for small applications that require persistent key-value storage without the overhead of full-fledged databases. It is designed for speed and ease of use, with a JSON-based storage format. -
17
sentinel
Sentinel is a filesystem-backed document DBMS written in Rust.
Sentinel is a filesystem-backed document DBMS built in Rust that prioritizes compliance, transparency, and auditability over raw performance. Unlike traditional databases, every document is a plain JSON file, making your data immediately forensic-friendly and Git-versionable. Perfect for regulated industries requiring GDPR, SOC 2, HIPAA, or PCI-DSS compliance. Sentinel provides async operations with automatic BLAKE3 hashing and optional Ed25519 signatures for cryptographic integrity. Data encryption supports AES-256-GCM, XChaCha20-Poly1305, and Ascon-128. Each document includes full audit metadata—creation timestamps, version history, hashes, and signatures—viewable with standard UNIX tools. Designed for edge deployments, compliance systems, audit logs, certificate management, and regulatory reporting. No server required, works entirely on filesystem with Git-based replication. Zero vendor lock-in—migrate anytime using standard tools like rsync, tar, or git. -
18
sled
The champagne of beta embedded databases
Serializable (ACID) transactions for atomically reading and writing to multiple keys in multiple keyspaces. Fully atomic single-key operations, including compare and swap. Forward and reverse iterators over ranges of items. A crash-safe monotonic ID generator capable of generating 75-125 million unique ID's per second. Zstd compression (use the compression build feature, disabled by default). Cpu-scalable lock-free implementation. Flash-optimized log-structured storage. Uses modern b-tree techniques such as prefix encoding and suffix truncation for reducing the storage costs of long keys with shared prefixes. If keys are the same length and sequential then the system can avoid storing 99%+ of the key data in most cases, essentially acting like a learned index. sled performs prefix encoding on long keys with similar prefixes that are grouped together in a range, as well as suffix truncation to further reduce the indexing costs of long keys.
