Redis

One of the most exciting things about Redis 8 is that it's open source under the AGPLv3 license. Rowan Trollope explains why we added the OSI-approved license, and how it's going to help us build a better Redis for our users going forward.

🚨Redis 8 is GA today.🚨 It's fast, loaded with new features, comes with the tools in Redis Stack included – and it's open source. Here's what you get with Redis 8: ▶️ It’s available under the open source, OSI-compliant AGPLv3 licence, as well as the existing dual RSALv2 and SSPLv1 licenses. ▶️ Modules and client packages that were previously shipped separately as Redis Stack are now included in Redis 8 ▶️ New data structures: Vector sets, a new native data type for vector similarity search built by Salvatore Sanfilippo, the creator of Redis; JSON for storing JSON documents as keys; time series for working with time stamped data; and probabilistic data structures including Bloom and Cuckoo filters and more ▶️ Redis Query Engine for advanced search and query features ▶️ Access Control Lists for fine-grained security control ▶️ Significant performance improvements for both single-core and multi-core environments, including an 87% reduction in command latency, 2x more ops per second throughput by enabling multithreading, 35% less memory use for replication, and 16x more query processing power with horizontal & vertical scaling ▶️ New libraries including Redis vector library for GenAI use cases, open source client libraries, mapping libraries and more ▶️ Full compatibility with Redis Insight and Redis for VS Code, visual tools that let you explore data, design, develop, and optimize your apps Get started here: https://lnkd.in/g-vWnYzK

We're thrilled to announce a 90-day Memurai Enterprise free trial! 🎉 Register through the new Memurai Portal to experience the production-ready Enterprise Edition—with no restrictions—for 90 days, now with Memurai 4.2.0. What’s New in 4.2.0?  🚀 Performance: Lower latency, better memory management, and optimized CPU efficiency.  🛠️ Capabilities: New commands, parameters, and APIs for improved data handling.  📊 Observability: Enhanced metrics for deeper system insights.  🛡️ Reliability: Strengthened security and stability. Try it now and power up your mission-critical apps: https://lnkd.in/dsH7Dzne Get the full power of Redis on Windows—with native support and production-ready scalability. #Memurai #DataStore #Caching #FreeTrial

The road to Redis 8 More than 15 years ago, Redis started with but a single person. Today, it powers the biggest platforms on the Internet. Join Guy Royse, Kyle Banker, Raphael De Lio, and Ricardo Ferreira as they trace Redis’ evolution—from its humble beginnings with strings and sets, through innovations like streams, search, and probabilistic structures, to the cutting edge of vector search and the upcoming release of Redis 8. We’ll talk tech, swap stories, and share insights about how Redis scaled—and continues to scale—to support companies like Twitter, GitHub, and StackOverflow. And we’ll explore where Redis is headed next. Reflect on Redis’ journey. Look ahead to its future. And hang out with the folks who live and breathe Redis every day.

Principal Developer Advocate Ricardo Ferreira is wrapping up his LLM Session Management mini-series by sharing additional Redis AI resources like Redis University courses for all skill levels, resources on GitHub, and our blogs. If you haven’t tuned in yet, head to our YouTube page where Ricardo dives into how developers can:  ▶️ Implement AI applications using LangChain and Redis ▶️ Create a new database on Redis Cloud ▶️ Use Redis as a vector store from LangChain ▶️ + More Catch up today: https://lnkd.in/gnWUX5FC

If you’re using Redis only to store strings, you’re seriously underusing it. Redis has been known since day one as a data structure server because of all the built-in data structures it supports. Here are the ones you need to know: 1 // Strings – Basic key-value storage ► https://lnkd.in/e6axnfc5 2 // JSON – Store and query JSON documents, use Redis as a Document DB ► https://lnkd.in/eyTnRUpm 3 // Lists – Ordered collection, great for queues/stacks ► https://lnkd.in/eKW-Eqdi 4 // Sets – Unordered, unique values; fast membership check ► https://lnkd.in/eBVKvY49 5 // Hashes – Store many key-value pairs in one Redis key, great for modeling data ► https://lnkd.in/ePiNEzkg 6 // Sorted Sets – Like Sets, but with scores for sorting, great for ranking ► https://lnkd.in/evVP7nnd 7 // Vector Sets – For storing and searching high-dimensional vectors, use Redis as a Vector DB ► https://lnkd.in/ekDK6meQ 8 // Streams – Log-like data structure, great for messaging, streaming, and event-driven applications ► https://lnkd.in/eVHWDtz7 9 // Bitmaps – Track true/false states using bits ► https://lnkd.in/e6aUwdMS 10 // Bitfields – More control over groups of bits, good for compact data storage ► https://lnkd.in/eXNn--s6 11 // Geospatial – Store lat/lon points and query by radius ► https://lnkd.in/evCMriiF 12 // HyperLogLogs – Approximate unique count using low memory ► https://lnkd.in/eP3Rictp 13 // Bloom Filters – Fast, memory-efficient membership test ► https://lnkd.in/ePjgM4NX 14 // Cuckoo Filters – Like Bloom Filters but allow deletion ► https://lnkd.in/ei7FFSyz 15 // t-digest – Approximate percentile queries on streaming data ► https://lnkd.in/e_QTFDUp 16 // Top-K – Keep track of the most frequent items using low memory ► https://lnkd.in/eWsNWM4z 17 // Count-Min Sketch – Estimate frequency of items with low memory ► https://lnkd.in/eT5PBcG7 18 // Time Series – Store and analyze time-stamped data, great for IoT ► https://lnkd.in/eBG-VTCQ Redis is more than a cache. It’s an in-memory (first) Swiss army knife. P.S. Know someone still using Redis just for strings? Share this with them.

Building AI apps with LLMs requires maintaining conversation context for better, more accurate responses. Watch how our Principal Developer Advocate Ricardo Ferreira shares how developers can leverage LangChain and Redis to implement efficient memory management for their AI applications in our new series: LLM Session Management with Redis.

If your building agents with LangGraph (and most enterprise customers i talk to these days are!).. Redis provides a unified data platform and has out-of-the-box integrations for Short-term memory (checkpointers), Long-term memory ( Store), LLM response caching (LLM Cache) and Context retrieval (vector store). Make your agents fast with Redis! Learn more here https://lnkd.in/g5bhC_Tq

Redis LangCache is now available in Private Preview! Sign up for the waitlist at redis.io/langcache See how you can Cache LLM responses easily to make your apps faster and save on LLM tokens (remember, agents are token guzzlers!)

Want faster, reusable LLM answers in your AI applications? While Redis offers speed and scale, semantic caching is key for reusing answers based on meaning, not just exact matches. Discover Redis’s semantic cache—capable of applying vector searches on previously stored answers. Redis Principal Developer Advocate Ricardo Ferreira shows how to implement this with LangChain and integrate it with an OpenAI-powered LLM in our latest series.