Loading...
Redis, while primarily an in-memory data store, offers vector search capabilities through its RediSearch and RedisAI modules, enabling vector similarity searches and deep learning model management for existing Redis users. With the RediSearch module, Redis extends its functionality to support native vector search, indexing, and hybrid queries, making it suitable for real-time AI and semantic search 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.
ClickHouse is an open-source column-oriented database that supports vectorized computation and now offers vector search features. Its architecture enables efficient real-time analytics and vector operations, making it a relevant choice for vector database use cases.
Datastax offers a vector search solution integrated with its database platform, enabling approximate similarity search and hybrid queries for enterprise use cases.
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.
Redis is an in-memory data store that supports a range of modern data workloads, including caching, vector search, and NoSQL database use cases. Through its RediSearch and RedisAI modules, Redis extends its capabilities to include native vector search, indexing, and hybrid queries, making it suitable for real-time AI and semantic search applications.
Redis offers multiple deployment options: