Neo4j Vector Search

MariaDB Vector is an extension or feature of MariaDB, providing capabilities for handling and querying vector data within the MariaDB ecosystem.

General-purpose, transactional, relational-graph-vector database that uses Datalog for queries. Embeddable but capable of handling large amounts of data and concurrency with HNSW indices for high-performance vector similarity searches.

An OpenSearch plugin that expands its capabilities with the custom `knn_vector` data type, enabling storage of embeddings and providing methods for k-NN similarity searches, including Approximate k-NN, Script Score k-NN, and Painless extensions.

Neural and hybrid search capability in OpenSearch that combines lexical queries with vector-based neural search using a pipeline of normalization and score combination techniques. It enables semantic (vector) search and hybrid search over indices such as `neural_search_pqa`, suitable for AI and vector database-style retrieval use cases.

A feature for MySQL that integrates vector store capabilities, allowing users to store and process vector embeddings for AI applications.

A unified knowledge graph and vector database solution built on Redis that seamlessly integrates graph traversal and vector similarity search for building advanced GenAI applications with both relational reasoning and semantic search capabilities.