Redis has released its new product named Redis Cloud Packages, a combination of pre-configured Redis Cloud instances designed to meet specific workloads and use cases, allowing users to skip from manual configurations and removing the hassle of managing Redis instances, making it more accessible and efficient for developers. Users can use a package for caching, NoSQL databases, or vector search.
Redis Cloud is designed to deliver a fully managed Redis database on major public cloud services. It provides users with all the features of Redis Enterprise, such as instant failover, backups and recovery, 24/7 monitoring and support, linear scalability, and predictable performance.
Redis as a Vector search aims to provide a foundation for AI applications from recommendation systems to document chat, allowing developers to ground their own virtual assistants utilizing agents and RAG (Retrieval Augmented Generation) to enhance responses from LLMs (Large Language Models). Furthermore, Redis Vector indexes are managed with similarity search. Users can choose between the following techniques: FLAT, a brute force approach, and HSNW, an approximate method utilizing Hierarchical Small Word graphs for efficient search. The metrics supported in Redis vector search to measure the similarity between two vectors are Euclidean, Inner Product, and Cosine. Users interested in exploring Redis Vector search can find resources on the Redis Learn section page.
Harrison Chase, co-founder and CEO of LangChain, stated:
"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."
RedisJSON is a high-performance NoSQL document store that provides native APIs to ingest, index, run queries and full-text search on JSON documents. Its main capabilities include:
- In-Memory JSON store - Store and process scheme-free JSON in-memory, supporting millions of operations per second
- Index and querying - it is possible to create indexes on JSON documents, perform complex aggregations, and filter by properties, numeric ranges, and geographical distance
- Full-text / fuzzy search - JSON supports full-text indexing and stemming-based query expansion in multiple languages, providing a rich query language that can perform text searches, as well as complex structured queries, and "fuzzy" searches
Let's see an example of the creation of a JSON document within a single Redis key named "testkey":
redis> JSON.SET testkey . '[ 123, { "life": 42 },{"fish","please"} ]'
OK
redis> JSON.GET testkey "[123,{\"life\":42},{\"fish\",\"please\"}]"
It is important to note that both Redis Enterprise and Redis Cloud are compatible with Redis Community Edition.
To get started, users can sign up with a Google or GitHub account and choose between the plans available. Currently there are three subscription plans:
- Free Redis Cloud Essentials - designed for training and prototyping purposes, it comes with 30MB storage and max 30 concurrent connections
- Redis Cloud Essentials (paid) - a cost-efficient option for low throughput scenarios; it comes with a storage capacity ranging from 250MB to 12GB, and 256 to Unlimited concurrent connections
- Redis Cloud Pro - this one supports more databases, greater throughput and unlimited connections compared to the Redis Cloud Essentials, it brings 50TB storage and unlimited concurrent connections
More details about subscriptions plans are available on the subscription page.
