Oracle's core database now includes vector search capabilities, enabling enterprises to perform scalable vector queries natively as part of their data management workflows. Oracle includes vector search capabilities in its database platform, supporting approximate KNN and hybrid search for enterprise-scale use cases.

Solr is a mature open-source search engine that has incorporated vector search capabilities, making it relevant for enterprises looking to implement vector-based search alongside traditional keyword search.

AWS has introduced vector search in several of its managed database services, including OpenSearch, Bedrock, MemoryDB, Neptune, and Amazon Q, making it a comprehensive platform for vector search solutions.

Elasticsearch is a distributed search engine supporting various data types, including vectors, and provides scalable vector search capabilities, making it a popular choice for modern AI-powered applications. It can be extended with the k-NN plugin to provide scalable vector search using HNSW and Lucene, enabling hybrid semantic and keyword search capabilities.

Google Vertex AI offers managed vector search capabilities as part of its AI platform, supporting hybrid and semantic search for text, image, and other embeddings.

Infinity is an AI-native database built for LLM applications, offering fast hybrid search of dense vectors, sparse vectors, tensors, and full-text data.