Meilisearch offers vector search capabilities as part of its search engine, enabling hybrid and semantic search for AI applications.

AstraDB (also known as Astra DB by DataStax) is a cloud-native vector database built on Apache Cassandra, supporting real-time AI applications with scalable vector search. It is designed for large-scale deployments and features a user-friendly Data API, robust vector capabilities, and automation for AI-powered applications.

ChromaDB (also known as Chroma or chroma-core) is an open-source vector database focused on LLM applications, emphasizing simplicity and in-memory HNSW-based dense vector search. It is suited for prototyping, metadata filtering, and offers a user-friendly interface for building and testing vector search applications, though it currently lacks hybrid and distributed features.

Datastax offers a vector search solution integrated with its database platform, enabling approximate similarity search and hybrid queries for enterprise use cases.

Deep Lake is a vector database designed as a data lake for AI, capable of storing and managing vector embeddings, text, images, and videos. It utilizes a tensor format for efficient querying and integration with AI algorithms, making it suitable for similarity search and machine learning workflows. It is open-source and tailored for handling unstructured and multimodal data, with seamless integration with frameworks like PyTorch and TensorFlow.

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.