30 open-source projects similar to infiniflow/infinity, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Infinity alternative.
LanceDB is a vector database and columnar data store designed to function as a versioned dataset manager and vector search engine. It serves as a high-performance backend for indexing and retrieving high-dimensional embeddings, providing the foundation for machine learning data pipelines. The system distinguishes itself through a combination of cloud-native object storage and immutable version tracking, allowing for data time-travel and reproducible AI experiments. It integrates hybrid search capabilities, merging dense vector similarity with BM25 full-text search and SQL-like scalar filters
zvec is an embedded vector database engine and indexing library designed for high-dimensional similarity search. It functions as a hybrid search engine and a retrieval-augmented generation knowledge base, allowing for the storage and retrieval of dense and sparse vectors. The system is distinguished by its hybrid retrieval pipeline, which fuses vector similarity, full-text keyword matching, and scalar metadata filtering into single query operations. It supports a plugin-based model integration system for registering custom embedding models and rerankers, as well as language bindings for nativ
RedisInsight is a graphical user interface and management tool for browsing, analyzing, and administering Redis databases. It provides a visual environment for exploring key-value data structures, managing database instances, and performing data analysis across different operating systems and deployments. The tool distinguishes itself by providing dedicated visual managers for complex operations, including a vector database manager for configuring embeddings and similarity searches, a query workbench for executing raw commands and Lua scripts, and a performance monitoring dashboard for tracki
TablePro is a cross-platform database management client designed for browsing, querying, and administering both SQL and NoSQL databases. It functions as a unified workspace that integrates a code-centric SQL editor with schema visualization tools, allowing developers to manage complex data models and execute queries across diverse database engines. The application distinguishes itself through an agentic AI integration layer that connects language models directly to database tools, enabling automated query generation, optimization, and error fixing with configurable approval gates. It features
RavenDB is a multi-model NoSQL document database designed for high-performance, ACID-compliant data storage. It persists structured information as schema-flexible JSON documents and utilizes a unit-of-work session pattern to track entity changes and batch modifications into atomic transactions. The platform is built on a distributed architecture that supports horizontal scaling through sharding and ensures high availability via multi-node, master-to-master cluster replication. The database distinguishes itself through a self-optimizing query engine that automatically creates and maintains ind
DeepLake is AI data infrastructure consisting of a multimodal data lake, a hybrid search engine, and a serverless vector database. It provides a PostgreSQL-based AI data runtime that combines multimodal storage with streaming pipelines to load and shuffle datasets from cloud storage directly into deep learning training pipelines. The system utilizes lazy indexing to store and slice images, audio, and video without loading entire files into memory. It enables retrieval-augmented generation by persisting high-dimensional embeddings in a serverless vector store and implementing hybrid search tha
This project is a software development kit and cluster management tool for PHP. It serves as a full-text search SDK and vector search interface, enabling applications to perform lexical, fuzzy, and semantic searches against indexed data. The library implements a PSR 7 HTTP client to ensure cross-environment compatibility through standardized messaging interfaces. It provides a specialized interface for retrieving embeddings and performing semantic retrieval workflows using vector data. Its capability surface covers a wide range of administrative and operational tasks, including search index
AliSQL is a fork of MySQL by Alibaba that extends the relational database management system with enhancements for high performance, scalability, and enterprise-grade availability. It retains the core MySQL identity as a SQL-based database for storing, organizing, and retrieving structured data, while adding optimizations for large-scale transactional and analytical workloads. The project differentiates itself through a set of Alibaba-specific improvements, including a columnar engine for accelerating analytical queries directly on MySQL tables, and a distributed, shared-nothing NDB Cluster en
Redis is a high-performance in-memory key-value store that functions as a distributed cache, message broker, and NoSQL database. It provides sub-millisecond read and write access to data stored in RAM and can operate as a vector database for indexing high-dimensional embeddings. The system supports a wide range of data storage and synchronization primitives, including the management of strings, hashes, lists, sets, and JSON documents. It enables real-time data operations through atomic transactions, hybrid persistence using snapshots and append-only logs, and high-availability configurations
Kvrocks is a disk-based NoSQL database and distributed key-value store that leverages the RocksDB storage engine to persist large datasets to physical disk. It is designed to be a Redis-compatible database, utilizing the standard Redis communication protocol to ensure interoperability with existing client libraries and tools. The project distinguishes itself by combining a disk-persistent storage model with advanced retrieval capabilities, including vector search for k-nearest neighbor queries, full-text search indexing, and geospatial query execution. It supports distributed clustering with
Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer
Trailbase is a backend-as-a-service platform delivered as a single executable that integrates a realtime database engine, an identity and access manager, and a type-safe API generator. It provides a comprehensive backend environment including a SQLite-backed storage engine and a WebAssembly runtime server for executing custom logic. The platform distinguishes itself by automatically transforming database schemas into JSON APIs with cross-language client bindings and by allowing the execution of portable components for server-side rendering and custom HTTP routes. It further incorporates vecto
This project is a reactive, offline-first NoSQL database engine designed for JavaScript applications. It provides a robust framework for managing application state by synchronizing data across browsers, mobile devices, and server-side runtimes. By treating local storage as the primary source of truth, it enables applications to remain functional without network connectivity, automatically reconciling changes with remote backends once a connection is restored. The database distinguishes itself through a modular architecture that supports cross-environment synchronization and high-performance d
Lance is a columnar data format and storage layer designed for high-performance random access and the persistence of multimodal data. It functions as a vector database storage system, a multimodal data store, and a versioned dataset manager. The project distinguishes itself as a hybrid search engine that combines vector similarity search and full-text indexing on a single dataset. It provides unified storage for diverse data types including images, audio, and video, utilizing a system that lazy-loads large binary objects only when requested. The system manages dataset evolution through schem
Lance is a versioned columnar data format and storage engine designed as a multimodal AI lakehouse. It serves as a vector database storage engine and a cloud object store dataset manager, organizing images, video, audio, and embeddings into a unified format optimized for machine learning workflows. The project distinguishes itself by combining a columnar layout for structured data with a specialized blob store for large multimodal tensors. It implements a hybrid search engine that integrates vector similarity search, full-text search, and SQL analytics on a single dataset, supported by a stor
Chroma is a specialized vector database designed to index and retrieve high-dimensional data representations for semantic similarity search. It functions as a comprehensive platform for information retrieval, enabling the storage and management of unstructured documents alongside structured metadata. By mapping data into numerical representations, the system facilitates rapid similarity lookups across large datasets. The platform distinguishes itself through a hybrid search infrastructure that combines dense vector embeddings with sparse keyword and regular expression matching to balance sema
Orama is a search engine and vector database that provides full-text indexing, geospatial calculations, and semantic vector storage. It functions as an LLM retrieval engine designed to provide grounded context to language models for conversational interfaces. The project implements hybrid search by combining dense vector embeddings with inverted keyword indices to retrieve documents based on both semantic meaning and exact text matches. It utilizes a WebAssembly module to execute search logic across different JavaScript environments and platforms. The system covers a broad range of retrieval
Manticoresearch is a high-performance search engine and database designed for indexing and retrieving large datasets. It functions as a full-text search engine, a vector search database, and a SQL-based search database, providing a distributed search cluster architecture. The system provides an alternative to the Elasticsearch stack, offering a compatible API for indexing and searching structured and unstructured data. It distinguishes itself by supporting multiple retrieval methods, including vector matching for similarity search, geospatial queries, and traditional full-text ranking. The p
ParadeDB is a database extension that integrates full-text search, vector database capabilities, and real-time analytics directly into a relational engine. It functions as a plugin that adds new storage and query execution capabilities to an existing database architecture. The project distinguishes itself by supporting hybrid search workflows that combine lexical keyword matching with dense and sparse vector similarity in a single query. It utilizes reciprocal rank fusion to merge these ranked result sets and employs logical replication to synchronize data from external instances, removing th
Hub is a multimodal AI data lake and vector database designed for storing and querying embeddings, text, audio, and images. It functions as a dataset version control system and a machine learning data streaming engine to support large-scale model training. The system utilizes a serverless PostgreSQL vector store to index high-dimensional embeddings for semantic search. It provides a visual interface for inspecting multimodal datasets and viewing annotations such as bounding boxes and masks. The platform handles cloud-agnostic storage synchronization and implements lazy, compressed data strea
Kvrocks is a distributed key-value store and Redis-compatible NoSQL database. It utilizes a RocksDB storage engine to provide disk-based persistence, allowing for high-capacity data storage with reduced memory costs compared to in-memory systems. The system functions as a vector database and full-text search engine, supporting nearest-neighbor searches on vector embeddings and complex document queries via text matching. It employs a proxyless cluster architecture with slot-based routing to distribute data and scale capacity across multiple nodes. The platform covers a wide range of data mana
Qdrant is a high-performance vector similarity database designed to store, index, and search high-dimensional vectors alongside structured metadata. It functions as a distributed search engine that manages large-scale data clusters, providing low-latency retrieval and complex filtering capabilities. The system is built to serve as a specialized middleware layer, connecting machine learning pipelines and AI agents to persistent storage for intelligent information retrieval and recommendation tasks. The platform distinguishes itself through advanced retrieval techniques, including support for h
Kùzu is an embedded property graph database engine designed for high-performance analytical queries and local data management. It operates as a library within the host application process, utilizing a columnar-based storage architecture and just-in-time query compilation to execute complex graph traversals and pattern matching efficiently. By mapping database files directly into system memory, it ensures data durability and high-speed access while maintaining ACID-compliant transactional integrity. The engine distinguishes itself by integrating vector similarity search and full-text search di
langchaingo is an LLM application framework for Go designed for building language model-powered applications and autonomous agents. It serves as an orchestration library and tool integration framework that allows developers to link prompt sequences and model calls into complex, multi-step workflows. The project provides a toolkit for implementing retrieval-augmented generation pipelines by processing unstructured documents and retrieving relevant context via vector search. It includes a dedicated integration layer for indexing high-dimensional embeddings and performing similarity searches acr
llmware is a Python framework for AI agent orchestration and model management, designed to coordinate multi-model workflows and autonomous agents. It provides a unified model catalog and standardized interface to execute specialized language models for complex research, analysis, and structured data generation. The project distinguishes itself through its heavy emphasis on local execution and quantized inference, allowing models to run on private infrastructure using CPU, GPU, and NPU acceleration via runtimes like ONNX and OpenVino. It features a specialized ability to translate natural lang
supabase-js is a comprehensive client library designed to integrate frontend applications with a hosted backend-as-a-service. It provides a unified interface for interacting with a PostgreSQL database, identity management systems, cloud object storage, and real-time data synchronization. The library features an isomorphic client design that operates across both browser and server environments. It distinguishes itself through a type-safe approach, utilizing TypeScript to map database schemas directly to client-side definitions, and employs a PostgREST-based API to translate JavaScript calls in
Elasticsearch is a distributed search engine and NoSQL document store designed for full-text search and real-time data retrieval. It functions as a RESTful data indexer and vector database, allowing for the storage and management of structured JSON documents across multiple nodes. The system distinguishes itself through its ability to serve as a log analytics platform for monitoring system health and security events. It incorporates vector search implementation using mathematical embeddings to support generative AI and augmented generation applications. The platform covers a broad range of c
Godis is a Redis-compatible in-memory database and distributed key-value store. It functions as a replicated data store and distributed message broker, implementing the Redis protocol to manage complex data structures in memory. The system provides a geospatial indexing engine for proximity-based queries and distance calculations. It ensures high availability and data durability through master-slave replication and write-ahead logging. The project covers a wide range of capabilities including the management of strings, hash maps, lists, and sorted sets. It supports distributed data clusterin
Ignite is a distributed in-memory data grid and compute platform. It functions as a distributed SQL database and storage engine designed to store and process large datasets in RAM to minimize latency and increase calculation speed. The system is distinguished by a multi-tier storage engine that manages data placement across memory and disk to balance high-speed access with large capacity. It features a distributed compute grid that executes custom logic directly on the nodes where data resides to reduce network traffic. The platform provides a broad set of capabilities including ACID transac
LibSQL is a high-performance, distributed SQL database engine that extends SQLite to support remote network access, edge computing, and real-time synchronization. It functions as an embedded database library that integrates directly into application processes while providing the infrastructure to maintain consistency across multiple geographic regions. The platform distinguishes itself by enabling database interaction over standard HTTP protocols, allowing applications to query remote data sources in serverless and edge environments without requiring local filesystem access. It includes nativ