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Showing content from https://python.langchain.com/v0.1/docs/integrations/retrievers/self_query/ below:

Self-querying retrievers | 🦜️🔗 LangChain

This is documentation for LangChain v0.1, which is no longer actively maintained. Check out the docs for the

latest version here

.

This is documentation for LangChain v0.1, which is no longer actively maintained.

Self-querying retrievers

Learn about how the self-querying retriever works here.

📄️ Deep Lake

Deep Lake is a multimodal database for building AI applications

📄️ Astra DB (Cassandra)

DataStax Astra DB is a serverless vector-capable database built on Cassandra and made conveniently available through an easy-to-use JSON API.

📄️ Chroma

Chroma is a vector database for building AI applications with embeddings.

📄️ DashVector

DashVector is a fully managed vector DB service that supports high-dimension dense and sparse vectors, real-time insertion and filtered search. It is built to scale automatically and can adapt to different application requirements.

📄️ Databricks Vector Search

Databricks Vector Search is a serverless similarity search engine that allows you to store a vector representation of your data, including metadata, in a vector database. With Vector Search, you can create auto-updating vector search indexes from Delta tables managed by Unity Catalog and query them with a simple API to return the most similar vectors.

📄️ DingoDB

DingoDB is a distributed multi-mode vector database, which combines the characteristics of data lakes and vector databases, and can store data of any type and size (Key-Value, PDF, audio, video, etc.). It has real-time low-latency processing capabilities to achieve rapid insight and response, and can efficiently conduct instant analysis and process multi-modal data.

📄️ Elasticsearch

Elasticsearch is a distributed, RESTful search and analytics engine.

📄️ Milvus

Milvus is a database that stores, indexes, and manages massive embedding vectors generated by deep neural networks and other machine learning (ML) models.

📄️ MongoDB Atlas

MongoDB Atlas is a document database that can be

📄️ MyScale

MyScale is an integrated vector database. You can access your database in SQL and also from here, LangChain.

📄️ OpenSearch

OpenSearch is a scalable, flexible, and extensible open-source software suite for search, analytics, and observability applications licensed under Apache 2.0. OpenSearch is a distributed search and analytics engine based on Apache Lucene.

📄️ PGVector (Postgres)

PGVector is a vector similarity search package for Postgres data base.

📄️ Pinecone

Pinecone is a vector database with broad functionality.

📄️ Qdrant

Qdrant (read: quadrant) is a vector similarity search engine. It provides a production-ready service with a convenient API to store, search, and manage points - vectors with an additional payload. Qdrant is tailored to extended filtering support.

📄️ Redis

Redis is an open-source key-value store that can be used as a cache, message broker, database, vector database and more.

📄️ Supabase (Postgres)

Supabase is an open-source Firebase alternative.

📄️ Tencent Cloud VectorDB

Tencent Cloud VectorDB is a fully managed, self-developed, enterprise-level distributed database service designed for storing, retrieving, and analyzing multi-dimensional vector data.

📄️ Timescale Vector (Postgres)

Timescale Vector is PostgreSQL++ for AI applications. It enables you to efficiently store and query billions of vector embeddings in PostgreSQL.

📄️ Vectara

Vectara is the trusted GenAI platform that provides an easy-to-use API for document indexing and querying.

📄️ Weaviate

Weaviate is an open-source vector database. It allows you to store data objects and vector embeddings from

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