# DigitalOcean Vector Databases – DigitalOcean Documentation > DigitalOcean Vector Databases let you store and search vector embeddings for retrieval-augmented generation, semantic search, and other AI workloads, using Weaviate, OpenSearch, or PostgreSQL as the underlying engine. ## DigitalOcean Managed Weaviate DigitalOcean Managed Weaviate is a fully managed Weaviate vector database for retrieval-augmented generation, semantic search, and similarity-based AI workloads. - [Weaviate Benchmarks](https://docs.digitalocean.com/products/vector-databases/weaviate/benchmarks/index.html.md): Throughput, latency, and recall measurements for the small, medium, and large Managed Weaviate tiers. - [Ingest and Retrieve Data on Managed Weaviate](https://docs.digitalocean.com/products/vector-databases/weaviate/ingest-and-retrieve/index.html.md): Define a collection, load objects with DigitalOcean Serverless Inference embeddings, and run hybrid, vector, and keyword searches against a Managed Weaviate cluster. ## DigitalOcean Managed OpenSearch for Vector Search Use DigitalOcean Managed OpenSearch as a vector database. OpenSearch bundles the k-NN, ML Commons, and Neural Search plugins for vector similarity search, hybrid (vector plus keyword) search, and remote embedding models. - [Create an OpenSearch Vector Database Cluster](https://docs.digitalocean.com/products/vector-databases/opensearch/how-to/create/index.html.md): Provision a DigitalOcean Managed OpenSearch cluster sized for vector search from the Control Panel, the API, or doctl. - [Vector Search Quickstart for OpenSearch](https://docs.digitalocean.com/products/vector-databases/opensearch/getting-started/quickstart/index.html.md): Create a DigitalOcean Managed OpenSearch cluster, configure it as a vector store, index sample embeddings, and run a k-NN similarity query in about 15 minutes. - [Vector Search on OpenSearch](https://docs.digitalocean.com/products/vector-databases/opensearch/concepts/vector-search-on-opensearch/index.html.md): Background you need to make good decisions when designing a vector-search system on DigitalOcean Managed OpenSearch. - [Create a k-NN Index in OpenSearch](https://docs.digitalocean.com/products/vector-databases/opensearch/how-to/create-knn-index/index.html.md): Choose an engine, a space type, and HNSW parameters for an OpenSearch k-NN index that matches your vector workload. - [Index and Query Vectors via the OpenSearch API](https://docs.digitalocean.com/products/vector-databases/opensearch/how-to/index-and-query/index.html.md): Ingest single and bulk documents, run k-NN queries, and filter by metadata against a DigitalOcean Managed OpenSearch vector database. - [Run Hybrid (Vector plus Keyword) Searches in OpenSearch](https://docs.digitalocean.com/products/vector-databases/opensearch/how-to/hybrid-search/index.html.md): Combine BM25 keyword relevance with k-NN vector similarity using a search pipeline on DigitalOcean Managed OpenSearch. - [Register a Remote Embedding Model with ML Commons](https://docs.digitalocean.com/products/vector-databases/opensearch/how-to/ml-commons/index.html.md): Let DigitalOcean Managed OpenSearch call your embedding provider directly at ingest and query time, using the ML Commons plugin. ## DigitalOcean Managed PostgreSQL for Vector Search Use DigitalOcean Managed PostgreSQL with the pgvector and pgvectorscale extensions to store embeddings alongside relational data and run vector similarity search in SQL. - [Enable pgvector and Load Embeddings](https://docs.digitalocean.com/products/vector-databases/postgresql/how-to/load-embeddings/index.html.md): Enable the pgvector extension on DigitalOcean Managed PostgreSQL, design a table for embeddings, and insert vectors from psql, Python, Node.js, and Go. - [Vector Search Quickstart for PostgreSQL](https://docs.digitalocean.com/products/vector-databases/postgresql/getting-started/quickstart/index.html.md): Create a DigitalOcean Managed PostgreSQL cluster, enable pgvector, store embeddings, and run a similarity search in about 10 minutes. - [Index and Tune Vector Search on PostgreSQL](https://docs.digitalocean.com/products/vector-databases/postgresql/how-to/index-and-tune/index.html.md): Choose between HNSW and IVFFlat, understand pgvector distance operators, tune recall versus speed, and combine similarity search with SQL filters on DigitalOcean Managed PostgreSQL. - [Advanced Vector Workloads with pgvectorscale and Hybrid Search](https://docs.digitalocean.com/products/vector-databases/postgresql/how-to/advanced-workloads/index.html.md): Use pgvectorscale StreamingDiskANN for disk-resident vector search, combine full-text and vector search for better relevance, and build a minimal RAG pattern on DigitalOcean Managed PostgreSQL. ## Getting Started with DigitalOcean Vector Databases Quickstarts to go from zero to a first vector similarity query on DigitalOcean Vector Databases. - [DigitalOcean Vector Databases Quickstart](https://docs.digitalocean.com/products/vector-databases/getting-started/quickstart/index.html.md): Pick a vector database engine and create your first cluster on DigitalOcean. ## DigitalOcean Vector Databases How-Tos How to create, secure, and manage Vector Database clusters on DigitalOcean. - [How to Create a DigitalOcean Vector Database Cluster](https://docs.digitalocean.com/products/vector-databases/how-to/create/index.html.md): Provision a managed Vector Database cluster from the Control Panel, the API, or doctl, for Weaviate, OpenSearch, or PostgreSQL. ## DigitalOcean Vector Databases Concepts Background on vector embeddings, distance metrics, HNSW indexing, hybrid search, and other concepts that transfer across Weaviate, OpenSearch, and pgvector. - [Vector Search Concepts](https://docs.digitalocean.com/products/vector-databases/concepts/vector-search-concepts/index.html.md): Background on embeddings, distance metrics, exact versus approximate nearest-neighbor search, HNSW indexing, and hybrid search for DigitalOcean Vector Databases. - [Choosing Between OpenSearch, Weaviate, and pgvector](https://docs.digitalocean.com/products/vector-databases/concepts/choosing-an-engine/index.html.md): A decision guide for picking among DigitalOcean's three Managed Vector Database engines based on workload shape, existing infrastructure, and operational requirements. ## DigitalOcean Vector Databases Details Pricing, availability, limits, and other details for DigitalOcean Vector Databases. - [DigitalOcean Vector Databases Features](https://docs.digitalocean.com/products/vector-databases/details/features/index.html.md): Features of DigitalOcean Vector Databases by engine, including supported indexes, hybrid search, and built-in vectorization. - [DigitalOcean Vector Databases Pricing](https://docs.digitalocean.com/products/vector-databases/details/pricing/index.html.md): Pricing for DigitalOcean Vector Databases, including Weaviate SKUs, embedding token billing, and the existing managed database rates for OpenSearch and PostgreSQL. - [DigitalOcean Vector Databases Availability](https://docs.digitalocean.com/products/vector-databases/details/availability/index.html.md): Regional datacenter availability for DigitalOcean Vector Databases. - [DigitalOcean Vector Databases Limits](https://docs.digitalocean.com/products/vector-databases/details/limits/index.html.md): Known limits and preview-stage restrictions for DigitalOcean Vector Databases.