Redis Inc recently announced the unified release of Redis 7.2, which includes several new features like auto-tiering, native triggers, and a preview of an enhanced, scalable search capability that provides increased performance for query and search scenarios, including vector similarity search (VSS).
Redis is the company's flagship product, an open-source in-memory data store that functions as a database, cache, streaming engine, and message broker, facilitating communication between data services and applications that use different messaging protocols. With the launch of Redis 7.2, the company brings enhancements in performance, new commands, and improvements in manageability across all products and services, including open source, source-available, commercial cloud (e.g., Azure Cache for Redis, Redis Enterprise Cloud for AWS), software, and Kubernetes distributions.
The enhancement in performance applies to the auto-tiering feature, formerly known as Redis on Flash, enabling developers and operators to efficiently handle growing large datasets by maintaining frequently accessed data in memory and migrating less used data to SSD. According to the company, this results in over twofold improved throughput compared to the prior version and up to 70 percent reduced infrastructure expenses for managing extensive DRAM.
Another enhancement in response to growing challenges for generative AI applications is scalable search preview in Redis 7.2, which enables a higher query throughput, including VSS and full-text search. By blending sharding for seamless data expansion with efficient vertical scaling, the company claims it ensures optimal distributed processing across the cluster and improves query throughput by up to 16x compared to what was previously possible.
Furthermore, Redis 7.2 include triggers and functions, which makes it possible for developers to build and maintain real-time applications by moving business logic closer to the data while remaining inside Redis, providing lower latency. In a Redis blog post on triggers and functions, the authors explain:
This capability lets developers define events (called triggers) to execute functions closer to the data. That is, developers define business logic that executes in response to database events or commands. That speeds up the code and related interactions, because there is no wait to bring code from clients into the database.
Full JavaScript, as an example, looks like this:
#!js name=lib api_version=1.0
function answer(client, data) {
return client.call(‘ping’);
}
redis.registerFunction(‘playPingPong’, answer);
The company also adds Redis Data Integration (RDI), which is a feature in preview that transforms any dataset into real-time accessibility by incrementally bringing data from multiple sources to Redis. The feature allows developers to integrate with data sources such as Oracle Database, Postgres, MySQL, and Cassandra.
Finally, for Redis Enterprise Software users, a new cluster management user interface (UI) has been introduced, modeled after the company's cloud UI, ensuring a consistent experience that enables operators to access database information easier. In addition, by collaborating with the maintainers of five libraries (Jedis, node-redis, redis-py, NRedisStack, and Go-Redis), the company has enhanced consistency in user experience, documentation, governance, performance, and security.
Stephen O’Grady, Principal Analyst with RedMonk, said in a Redis press release:
One of the most important ways databases can improve their developer experience is by becoming more versatile by way of the addition of new capabilities and tools. By leveraging its broad developer community, Redis is looking to deliver a more versatile database and thus, a better developer experience.
However, a respondent on a Reddit thread commented:
Redis stopped development years ago. This is all closed-source overpriced enterprise software. But, like, crazily overpriced. I'm sorry I ever designed my startup with Redis as a database (and not just a basic cache). I would have never made such a deep reliance by design on an overpriced enterprise software. The OSS part of Redis is just a facade at this point.
Lastly, more information on Redis is available on the documentation pages.