2026 Meilleurs outils de Base de données vectorielle

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MongoDB

Base de données vectorielle

MongoDB est une plateforme de données moderne basée sur MongoDB Atlas pour le développement d’applications et les charges de production.

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SingleStore

Analytics & BI

A real-time database for transactional, analytical, and AI-driven applications.

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SurrealDB

Infrastructure pour agents IA

SurrealDB est une couche de contexte multimodèle pour agents IA, réunissant données documentaires, graphes, vectorielles, temporelles et relationnelles dans une transaction ACID.

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ParadeDB

Base de données vectorielle

ParadeDB ajoute la recherche, la récupération vectorielle et les agrégations à PostgreSQL.

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MyScale

Base de données vectorielle

MyScale queries vector and structured data with SQL. Build similarity and filtered retrieval over embeddings and metadata on a managed cloud cluster.

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Spice AI

Base de données vectorielle

Moteur open source de requêtes SQL et de recherche hybride pour applications riches en données et agents IA, sans ETL.

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Powabase

Infrastructure pour agents IA

A Postgres backend for AI applications with built-in retrieval, agents, auth, and storage.

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Ducky

Moteur de Recherche IA

Ducky est une plateforme de recherche et de récupération IA entièrement gérée pour créer des fonctionnalités RAG sur texte, images, PDF et données structurées.

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Vespa.ai

Moteur de Recherche IA

Vespa is an AI search platform for building search, retrieval-augmented generation, recommendation, personalization, and agent applications over text, vectors, tensors, and structured data. It is designed for developer teams that need configurable ranking and distributed operation at production scale.

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SereneDB

Base de données vectorielle

SereneDB is a search-OLAP database for real-time full-text, vector, hybrid search, and analytical queries over the same data. It uses SQL and the PostgreSQL wire protocol, helping developers connect with familiar clients while keeping search and analytics in one engine.

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Redis

Base de données vectorielle

Redis is a real-time data platform and database for applications, with Redis Cloud providing a fully managed deployment on major public cloud services. It supports application data, caching, search, and AI-oriented workflows through Redis and Redis Stack.

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Upstash Vector

Base de données vectorielle

Upstash Vector is a serverless vector database for storing and querying embeddings and metadata in AI and machine-learning applications. It supports dense, sparse, and hybrid indexes through a REST API and SDKs for Python, TypeScript, Go, and PHP.

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pgvector

Base de données vectorielle

pgvector is an open-source PostgreSQL extension for storing vectors and running exact or approximate nearest-neighbor searches alongside relational data. It supports multiple vector formats, distance functions, and standard PostgreSQL operations for applications that need similarity search.

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OpenSearch

Moteur de Recherche IA

OpenSearch is a community-driven, Apache 2.0-licensed open source search and analytics suite for ingesting, searching, visualizing, and analyzing data. It supports application search, observability, security analytics, and machine learning workflows.

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Weaviate

Base de données vectorielle

Weaviate is a vector database for building AI-native applications, including retrieval-augmented generation systems. It helps developers store and retrieve vector data, connect applications to language models, and deploy the database in a managed, self-hosted, or private-cloud environment.

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Supabase

Base de données vectorielle

Supabase is a Postgres development platform for building applications with a database, authentication, APIs, realtime features, serverless functions, storage, and vector support. It helps developers move from application code to a managed backend through a dashboard, client libraries, CLI, and generated APIs.

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turbopuffer

Moteur de Recherche IA

turbopuffer is an object-storage-native search engine for vector, full-text, hybrid, and regex search. It helps AI, search, and data teams retrieve content from large document collections with filtering, ranking, and scalable namespace-based storage.