Redis recently announced the unified release of Redis 7.2 across all of the company’s products and services, including open source, source-available, commercial cloud, software, and Kubernetes distributions. Redis Enterprise 7.2 cloud and software products preview a scalable search feature which delivers even greater performance for query and search use cases, including vector similarity search (VSS).
Redis 7.2 raises the bar for ease-of-use across the board from new core Redis capabilities to tooling while ensuring that the clients, integrations, and documentation deliver a seamless, unified experience. Additionally, with the growing challenges of building generative AI applications, Redis Enterprise has been enhanced to store vector embeddings while providing a high-performance index and query search engine.
Any Redis practitioner can now build better, faster, and more confidently, taking advantage of:
Scalable search, previewed in this release, enables a higher query throughput, including VSS and full-text search exclusively as part of the company’s commercial offerings. Redis Enterprise now achieves superior search performance by blending sharding for seamless data expansion with efficient vertical scaling. This ensures optimal distributed processing across the cluster and improves query throughput by up to 16x compared to what was previously possible.
Working directly with the community maintainers of the five most popular client libraries—Jedis (Java), node-redis (NodeJS), redis-py (Python), NRedisStack (.Net), and Go-Redis (Go)—Redis is driving consistency in the experience, documentation, governance, performance, and security across those libraries. Additionally, the latest version of the Redis Serialization Protocol (RESP3) is now supported across source-available, Redis Enterprise cloud and software products for the first time.
Developers can now program, store, and execute Triggers and Functions within Redis using Javascript. Previewed on Redis Enterprise Cloud in select regions, Triggers and Functions empower developers to build and maintain real-time applications by moving business logic closer to the data without leaving Redis, ensuring lower latency.
Auto Tiering (previously Redis on Flash) helps developers and operators cost-effectively manage large datasets with increasing volume. With Auto Tiering, operators can keep heavily used data in memory and move less frequently needed data to SSD. Auto Tiering offers more than twice the throughput of the previous version while reducing the infrastructure costs of managing large datasets in DRAM by up to 70 percent.
Redis Enterprise Software customers also have a new cluster management user interface (UI) inspired by the company’s cloud UI. This consistency allows operators to access the information they need on a database with a few clicks, which will reduce learning curves, improve resolution times, and minimize errors.
Redis Data Integration (RDI) transforms any dataset into real-time accessibility by seamlessly and incrementally bringing data from multiple sources to Redis. Through RDI, now in public preview, Redis Enterprise Software customers can integrate with popular data sources such as Oracle Database, Postgres, MySQL, and Cassandra, enabling greater performance and cost savings.
“Redis 7.2 is an exciting release because we’ve wrapped our arms around the end-to-end Redis experience and made it a top priority to ensure the tooling, integrations, and control users require to match the seamless ease-of-use that anyone who loves Redis expects,” said Rowan Trollope, CEO at Redis. “Redis has also been an early mover in the emergence of vector database technology. Scalable search further optimizes the processing of low-latency vector workloads with a robust and performant search engine to make it easy for developers to build generative AI applications.”
“As enterprises continue to look for ways to increase their velocity, many eyes are beginning to turn to developer experience as better developer experiences lead to happier and faster developers. Databases are no exception to this trend,” said Stephen O’Grady, Principal Analyst with RedMonk. “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.”
“Docugami’s Generative AI for Business Documents requires incredible speed and reliability for our Business Document Foundation Model and massively scalable document processing pipeline using Apache Spark,” said Jean Paoli, CEO and co-founder of Docugami, the industry leader in generative AI for business documents. “With Redis Enterprise as our vector database and our backing data store for Apache Spark, we’ve achieved superior latency, throughput, and embedding search result accuracy. Redis is helping us turn dense, lengthy documents into valuable data as a Document XML Knowledge Graph for our customers at massive scale.”
“iFood has been successfully managing terabytes of data with Redis Enterprise Cloud for our feature store databases,” said Daniel Galinkin, head of machine learning engineering at iFood. “High-performance solutions are at the heart of our business, so we are eager to see Redis continue to innovate on their memory capabilities, and we look forward to leveraging Auto Tiering to boost our service and seamless end-user experience.”
