Open Source Rust Database Software - Page 2
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Rust Database Software
View 467 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.
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Say goodbye to broken revenue funnels and poor customer experiencesLeanData is a Demand Management solution that supports all go-to-market strategies such as account-based sales development, geo-based territories, and more. LeanData features a visual, intuitive workflow native to Salesforce that enables users to view their entire lead flow in one interface. LeanData allows users to access the drag-and-drop feature to route their leads. LeanData also features an algorithms match that uses multiple fields in Salesforce.
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SurrealDB
A scalable, distributed, collaborative, document-graph database
With an SQL-style query language, real-time queries with highly-efficient related data retrieval, advanced security permissions for multi-tenant access, and support for performant analytical workloads, SurrealDB is the next generation serverless database. SurrealDB is the ultimate cloud database for tomorrow's applications. SurrealDB is an innovative NewSQL cloud database, suitable for serverless applications, jamstack applications, single-page applications, and traditional applications. It is unmatched in its versatility and financial value, with the ability for deployment on cloud, on-premise, embedded, and edge computing environments. For a hassle-free setup, get started with SurrealDB Cloud in one-click. There is no need for your team to learn new complicated database languages. Getting started with SurrealDB is as simple as one command - and advanced functionality is simple to understand, whilst still being fast and performant. -
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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. -
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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. -
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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. -
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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. -
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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). -
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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. -
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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. -
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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. -
Dominate AI Search ResultsAthenaHQ is a cutting-edge platform for Generative Engine Optimization (GEO), designed to help brands optimize their visibility and performance across AI-driven search platforms like ChatGPT, Google AI, and more.
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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. -
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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. -
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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.
