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Awesome GitHub RepositoriesVector Databases

Databases optimized for storing and querying high-dimensional vector embeddings.

Distinguishing note: Focuses on the storage technology used for semantic search.

Explore 68 awesome GitHub repositories matching data & databases · Vector Databases. Refine with filters or upvote what's useful.

Awesome Vector Databases GitHub Repositories

AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
  • open-webui/open-webuiopen-webui का अवतार

    open-webui/open-webui

    142,694GitHub पर देखें↗

    Open WebUI is a self-hosted, web-based platform designed for interacting with local and remote artificial intelligence models. It functions as a unified interface and orchestration suite, enabling users to build, deploy, and manage specialized AI agents equipped with custom instructions, external tool access, and private knowledge bases. The platform distinguishes itself through a modular architecture that supports complex AI workflows. It features a plugin-based framework for custom logic and pipeline-based request processing, allowing developers to filter or transform data streams before th

    Uses vector embeddings to store and query document collections for semantic searches.

    Pythonaillmllm-ui
    GitHub पर देखें↗142,694
  • elasticsearch/elasticsearchelasticsearch का अवतार

    elasticsearch/elasticsearch

    77,171GitHub पर देखें↗

    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

    Implements a database optimized for storing and querying high-dimensional vector embeddings for semantic search.

    Java
    GitHub पर देखें↗77,171
  • mem0ai/mem0mem0ai का अवतार

    mem0ai/mem0

    58,698GitHub पर देखें↗

    Mem0 is an agent-agnostic memory layer designed to provide intelligent agents with long-term persistence and cross-session state management. By acting as a centralized service, it allows diverse AI agents to recall user preferences, past interactions, and historical context, ensuring continuity across multiple workflows and independent agent systems. The platform distinguishes itself through a multi-signal retrieval engine that combines semantic vectors, keyword matching, and entity-linked metadata to surface the most relevant information. It employs an adaptive memory engine that automatical

    Stores unstructured user information as high-dimensional embeddings to enable semantic similarity searches across long-term interaction histories.

    Pythonagentsaiai-agents
    GitHub पर देखें↗58,698
  • crewaiinc/crewaicrewAIInc का अवतार

    crewAIInc/crewAI

    53,687GitHub पर देखें↗

    CrewAI is a multi-agent orchestration framework designed for building autonomous systems that execute complex, multi-step workflows. It provides a development platform where specialized agents are defined with specific roles, goals, and tool sets to perform tasks collaboratively. By leveraging a declarative workflow engine, the system manages task dependencies, state transitions, and execution logic, allowing for the creation of structured, stateful sequences of operations. The framework distinguishes itself through its hierarchical management capabilities, which utilize manager agents to coo

    Uses vector embeddings to retain and retrieve context across tasks for improved agent consistency.

    Pythonagentsaiai-agents
    GitHub पर देखें↗53,687
  • flowiseai/flowiseFlowiseAI का अवतार

    FlowiseAI/Flowise

    53,641GitHub पर देखें↗

    Flowise is a low-code platform designed for building and deploying complex language model workflows through a visual, node-based interface. It functions as an orchestrator for autonomous multi-agent systems, allowing users to construct conversational pipelines by connecting language models, memory stores, and external tools on a drag-and-drop canvas. The platform distinguishes itself through its support for sophisticated agentic patterns, including supervisor-worker delegation and iterative reasoning strategies. Users can design directed acyclic graphs to manage conditional branching, state p

    Indexes document data into vector databases for searchable information.

    TypeScriptagentic-aiagentic-workflowagents
    GitHub पर देखें↗53,641
  • clickhouse/clickhouseClickHouse का अवतार

    ClickHouse/ClickHouse

    48,229GitHub पर देखें↗

    ClickHouse is a high-performance, columnar analytical database designed for real-time query execution and large-scale data aggregation. It functions as a distributed data warehouse capable of processing petabytes of information, while also providing an embedded engine that integrates directly into applications for native query capabilities without external dependencies. The system is built to handle high-throughput ingestion and complex analytical workloads, delivering millisecond-level latency for interactive dashboards and operational monitoring. The platform distinguishes itself through ad

    Provides high-speed similarity matching and vector indexing capabilities for analytical workflows.

    C++aianalyticsbig-data
    GitHub पर देखें↗48,229
  • anthropics/claude-cookbooksanthropics का अवतार

    anthropics/claude-cookbooks

    45,835GitHub पर देखें↗

    This repository serves as a comprehensive library of architectural blueprints and code examples for integrating large language models into software applications. It functions as a developer learning resource, providing structured tutorials and implementation patterns that demonstrate how to build intelligent features using advanced prompting and data processing techniques. The collection distinguishes itself by focusing on complex reasoning and data-grounding workflows. It provides practical guidance on implementing retrieval-augmented generation pipelines, which connect language models to pr

    Transforms unstructured text into high-dimensional numerical vectors to enable efficient similarity searching and context-aware information retrieval.

    Jupyter Notebook
    GitHub पर देखें↗45,835
  • milvus-io/milvusmilvus-io का अवतार

    milvus-io/milvus

    44,804GitHub पर देखें↗

    Milvus is a specialized vector database engine designed for the indexing, management, and high-speed similarity retrieval of high-dimensional vector embeddings. It functions as a similarity search engine capable of identifying nearest neighbors within large-scale vector spaces, supporting the storage and retrieval of billions of data points while maintaining consistent performance. The system utilizes a distributed architecture that decouples storage, query, and coordination into independent services, allowing for horizontal scaling across clusters. It employs a global indexing mechanism that

    Functions as a specialized storage engine optimized for indexing and high-speed similarity retrieval of vector embeddings.

    Goannscloud-nativediskann
    GitHub पर देखें↗44,804
  • pingcap/tidbpingcap का अवतार

    pingcap/tidb

    40,166GitHub पर देखें↗

    TiDB is a horizontally scalable, distributed SQL database designed to provide consistent transactional storage and high-performance analytical processing within a single unified architecture. It utilizes a decoupled compute-storage design and a distributed key-value storage layer to ensure horizontal scalability and efficient range-based queries. By employing a consensus-based replication algorithm, the system maintains high availability and automatic failover across multiple nodes and geographical regions. The platform distinguishes itself through its hybrid transactional and analytical proc

    A storage engine that integrates high-dimensional vector embeddings to perform semantic similarity searches alongside traditional relational data queries.

    Gocloud-nativedatabasedistributed-database
    GitHub पर देखें↗40,166
  • danny-avila/librechatdanny-avila का अवतार

    danny-avila/LibreChat

    39,276GitHub पर देखें↗

    LibreChat is an artificial intelligence orchestration platform that provides a unified interface for interacting with multiple language models. It functions as a centralized workspace where users can switch between different intelligence engines, manage complex conversational workflows, and maintain persistent memory across sessions through a vector-database-backed storage system. The platform distinguishes itself through an extensible agent framework that supports autonomous task execution and the integration of external tools. It features a secure, containerized environment for executing co

    Enables long-term memory and semantic retrieval by storing conversational context and history within a vector database.

    TypeScriptaianthropicartifacts
    GitHub पर देखें↗39,276
  • typeorm/typeormtypeorm का अवतार

    typeorm/typeorm

    36,540GitHub पर देखें↗

    TypeORM is an object-relational mapper for TypeScript and JavaScript that bridges the gap between object-oriented application code and relational database tables. It provides a comprehensive data persistence layer that allows developers to define database entities using class decorators or configuration objects, enabling seamless interaction with data through object-oriented patterns. The project distinguishes itself through a flexible architecture that supports both the data mapper and repository patterns, alongside a fluent query builder that translates high-level method calls into platform

    Executes similarity searches using distance metrics like Euclidean and cosine distance.

    TypeScriptactive-recordcockroachdbdata-mapper
    GitHub पर देखें↗36,540
  • dokploy/dokployDokploy का अवतार

    Dokploy/dokploy

    34,901GitHub पर देखें↗

    Dokploy is a self-hosted platform-as-a-service designed to simplify the deployment and management of containerized applications and databases. It provides a centralized control plane that decouples administrative management from application workloads, allowing users to oversee infrastructure across multiple server nodes through a unified web interface or a command-line tool. The platform distinguishes itself through an extensive library of pre-configured application templates, enabling the rapid deployment of databases, identity providers, and various productivity or development tools. It sup

    Provides a high-performance vector search engine for machine learning applications.

    TypeScriptbackendbackupsdatabases
    GitHub पर देखें↗34,901
  • qdrant/qdrantqdrant का अवतार

    qdrant/qdrant

    32,372GitHub पर देखें↗

    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

    Stores, indexes, and searches high-dimensional vectors alongside structured metadata for intelligent retrieval applications.

    Rustai-searchai-search-engineembeddings-similarity
    GitHub पर देखें↗32,372
  • chroma-core/chromachroma-core का अवतार

    chroma-core/chroma

    26,198GitHub पर देखें↗

    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

    Indexes and retrieves high-dimensional data representations for efficient semantic similarity search and analysis.

    Rustaidatabasedocument-retrieval
    GitHub पर देखें↗26,198
  • typesense/typesensetypesense का अवतार

    typesense/typesense

    25,254GitHub पर देखें↗

    Typesense is a distributed search engine designed to provide sub-millisecond query latency across massive datasets. It functions as both a high-performance indexing and retrieval engine and a comprehensive search experience platform, offering built-in typo tolerance and tools for managing relevance through synonym configuration, result curation, and complex filtering. The platform distinguishes itself by utilizing in-memory indexing to maintain high-throughput data retrieval and integrating vector database capabilities to support semantic similarity searches. It ensures data consistency and h

    Manages high-dimensional embeddings to facilitate semantic search and natural language processing tasks.

    C++algoliadatastoreelasticsearch
    GitHub पर देखें↗25,254
  • rohitg00/agentmemoryrohitg00 का अवतार

    rohitg00/agentmemory

    23,785GitHub पर देखें↗

    AgentMemory is a persistent knowledge store and memory server designed to provide AI coding agents with long-term memory. It functions as a knowledge graph engine and vector database store that saves and recalls project context, architectural decisions, and patterns across different sessions. The system distinguishes itself by using a tiered-memory consolidation pipeline that compresses raw observations into episodic, semantic, and procedural layers to optimize token usage. It employs a hybrid retrieval strategy combining keyword matching, vector embeddings, and graph traversal to surface rel

    Provides a vector database for storing high-dimensional embeddings of project observations and facts.

    TypeScriptagentmemoryagentsai
    GitHub पर देखें↗23,785
  • redis/go-redisredis का अवतार

    redis/go-redis

    22,159GitHub पर देखें↗

    This project is a feature-rich Go client library designed for interacting with Redis. It serves as a comprehensive interface for managing remote data stores, enabling developers to execute standard database commands, handle complex data structures, and perform asynchronous operations within Go applications. The library distinguishes itself through its support for advanced Redis capabilities, including connection pooling, pipelining, and transactional integrity. It provides specialized primitives for managing distributed clusters, including automated topology updates and request routing to sha

    Executes mathematical and data transformation operations directly within the database memory space.

    Gogogolangredis
    GitHub पर देखें↗22,159
  • pgvector/pgvectorpgvector का अवतार

    pgvector/pgvector

    21,787GitHub पर देखें↗

    Vector similarity search extension for PostgreSQL.

    Executes distance calculations and transformations directly within the database memory to minimize latency.

    Cpostgresvector-searchembeddings
    GitHub पर देखें↗21,787
  • hkuds/rag-anythingHKUDS का अवतार

    HKUDS/RAG-Anything

    21,372GitHub पर देखें↗

    RAG-Anything is a retrieval-augmented generation framework designed to index diverse document formats and perform semantic search using local machine learning models. It functions as a local multimodal data processor, extracting and organizing information from various file types into a unified knowledge base to facilitate private document analysis. The system distinguishes itself through its high-throughput ingestion engine, which processes large batches of documents into searchable vector embeddings. By executing machine learning models directly on local hardware, the framework ensures that

    Ingests large batches of documents into searchable vector embeddings for efficient retrieval.

    Pythonmulti-modal-ragretrieval-augmented-generation
    GitHub पर देखें↗21,372
  • tursodatabase/libsqltursodatabase का अवतार

    tursodatabase/libsql

    16,887GitHub पर देखें↗

    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

    Stores and queries high-dimensional vector embeddings natively within the database engine.

    Cdatabaseembedded-databaserust
    GitHub पर देखें↗16,887
पिछला123…4अगला
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सब-टैग एक्सप्लोर करें

  • Distributed ArchitecturesVector databases designed to be deployed as clusters across multiple nodes for scalability and availability. **Distinct from Vector Databases:** Distinct from Vector Databases: specifically focuses on the distributed, clustered nature of the deployment for high availability.
  • In-Process ComputationExecution of mathematical operations directly within the database memory space. **Distinct from Vector Databases:** Distinct from Vector Databases: focuses on the execution location and latency optimization rather than the storage model.
  • Integration TutorialsInstructional guides on connecting applications to vector stores for semantic search and retrieval. **Distinct from Vector Databases:** Focuses on the educational tutorial aspect of integration rather than the database software or connectors themselves
  • Relational Vector EnginesDatabase systems that unify relational SQL analytics with high-dimensional vector storage for AI applications. **Distinct from Vector Databases:** Distinct from standard vector databases: focuses on the hybrid capability of combining SQL relational storage with vector similarity search.
  • TemporalVector databases that incorporate time-travel capabilities for historical state retrieval. **Distinct from Vector Databases:** Combines vector similarity search with temporal versioning, whereas standard vector databases are typically non-temporal.
  • Vector Aggregation1 सब-टैगFunctions for calculating mathematical averages and summaries across groups of vectors. **Distinct from Vector Databases:** Distinct from Vector Databases: focuses on the aggregation operation specifically rather than the database system.
  • Vector Database Management ToolsVisual interfaces for the administration of vector storage, schemas, and embeddings. **Distinct from Vector Databases:** Focuses on the visual management tool for vector databases rather than the underlying database engine itself.
  • Vector IngestionProcesses and loads multimodal data and embeddings into vector databases. **Distinct from Vector Databases:** Focuses on the ingestion process into vector stores, whereas the parent describes the storage technology itself.
  • Vector Manipulations2 सब-टैग्सTools for extracting and processing vector embeddings within database queries. **Distinct from Vector Databases:** Distinct from Vector Databases: focuses on the query-time manipulation of vector data rather than the storage engine itself.