Get superior speed and throughput
Deliver fast responses that go beyond predictive analytics to create new experiences with GenAI in real-time, including chatbots that offer personalized support. We support retrieval-augmented generation (RAG) workflows and similarity searches to deliver answers quickly, and provide the fastest performance across all leading vector databases that we benchmark.
Integrate with more data and AI tools
Get rich support for integrations and diverse data types to bring AI apps to production faster. Move quickly with a database that works with your existing tech stack and the latest GenAI tools and frameworks. Whether you’re in the cloud, on prem, or using a hybrid environment, build resilient apps and move at the speed of innovation.
Trusted by the world’s largest organizations
58% of Fortune 50 companies trust our global scale and enterprise power. Built on our real-time platform, our vector database lets you scale apps worldwide and deliver the fastest experiences with sub-millisecond latency and 99.999% uptime. Optimize your data infrastructure at any scale with multi-tenancy, Redis Flex, and built-in durability.
“We’re using Redis Cloud for everything persistent in OpenGPTs, including as a vector store for retrieval and a database to store messages and agent configurations. The fact that you can do all of those in one database from Redis is really appealing.”
Harrison Chase
Co-Founder and CEO, LangChain
“We are very happy with Redis because it allows us to do a better job faster and more reliably… It is a fast, high-performance vector database—and Redis is a wonderful partner.”
Taqi Jaffri
Co-founder and Head of Product, Docugami
“Our real-time recommender infrastructure needs to search and update vector embeddings in milliseconds to deliver a blazing fast experience for our marketplace, e-commerce and social customers. We benchmarked all the leading vector databases on the market, and Redis Cloud came out on top.”
Daniel Svonava
Co-founder, Superlinked
Learn more about Redis vector database on our docs site
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