Redis

Redis

@redis.io

See how fast feels https://redis.io/

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Redis reposted

Replying to @cassidoo.co

This week's sponsor is @redis.io! Ever notice your agents just...forget everything the second a session ends? Redis Agent Memory fixes that. It gives your agents short-term memory plus context that actually sticks around across conversations, managed for you. redis.io/agent-memory...

redis.ioRedis Agent Memory | RedisDevelopers love Redis. Unlock the full potential of the Redis database with Redis Enterprise and start building blazing fast apps.
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➡️ Working memory vs. long-term memory, and when an agent should write to each ➡️ How Redis Context Retriever (the tool at the heart of Redis Iris) auto-generates business entities and exposes them as MCP tools ➡️ Why semantic caching with LangCache turns paraphrased repeat queries into cache hits

➡️ How Redis Data Integration keeps agent context fresh from your source databases without manual stitching ➡️ The cold-cache vs. warm-cache latency difference, measured live. If you're building agents, or agent infrastructure, watch this today.

It goes deep on how to fix that using Redis Iris, our real-time context engine, and walks through building a wealth advisor agent live, from end to end. Here's what you'll learn:

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More upgrades: ➡️ Hash subkey notifications — subscribe to field-level events ➡️ Multiple time series aggregators in one command (hello, candlestick charts) ➡️ Explicit JSON float storage: BF16/FP16/FP32/FP64 ➡️ New COUNT aggregator for sorted set unions/intersections

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Rate limiting is one of the most common Redis patterns, and it used to need Lua. Not anymore. The new INCREX command gives you a window counter rate limiter natively, with bounds and expiration control built in.

Streams get NACKing. The new XNACK command lets consumers explicitly release pending messages, so they're immediately re-delivered to other consumers instead of sitting idle in the PEL. SILENT, FAIL, and FATAL modes map to real-world failure scenarios.

Redis Array: a new general-purpose data structure created by @antirez.bsky.social. Index-addressable, dynamic, sparse-friendly, and compute-aware. Fast access by index, sliding windows, and server-side SUM/MIN/MAX. Its ARRING command does ring buffers at 2x the throughput of RPUSH+LTRIM

Agents 🤝 Ham radio 🤝 Guy Royse—it's a match made in AI heaven. Be sure to watch Guy build Earshot, his transcription agents that captures ham radio chatter as it happens, live this Thursday, June 4 at 9am PT as part of Microsoft's VS Code Live.

Guy Royse@guy.dev

I built Earshot. Agents listen to audio (a mic and my ham radio), transcribe it, and write it to shared memory. A chatbot reads it and chats about it. The interesting bit, the agents never talk directly. They just share memory. Agent coordination is just decoupling. github.com/redis-develo...

Uber’s CacheFront serves 150M+ reads per second with 99.9%+ cache hit rates, and does it while maintaining strong consistency guarantees.

Their secret? Treating cache as a first-class part of the data system, not an afterthought. By integrating Redis directly into the write path, Uber tackled one of the hardest problems in distributed systems: cache invalidation at massive scale.

Redis Open Source 8.4 is now GA. It’s faster, more scalable, and now has hybrid search. It’s the most advanced version of Redis yet, continuing our mission to make Redis faster, simpler, and more powerful.

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Redis Open Source 8.4 is now GA. It’s faster, more scalable, and now has hybrid search. It’s the most advanced version of Redis yet, continuing our mission to make Redis faster, simpler, and more powerful.

New features include: 🔎 Hybrid search: Combines full-text and vector results in one query, for more accurate AI, RAG, and semantic search. 📈 Performance improvements: Multi-threaded I/O, improved memory handling + smarter JSON storage delivers 30% higher throughput, 91% lower memory use.

We worked with @deeplearningai.bsky.social to create a new course called "Semantic Caching for AI Agents." Redis experts will help you build a semantic cache that makes AI agents faster and more cost-effective by recognizing when different questions mean the same thing.

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In this course, you'll learn how to build a semantic cache that reuses responses based on meaning, not exact text matches, as well as: • Measure cache performance • Enhance accuracy with cross-encoders & LLM validation • Build caching into an AI agent that's faster + more cost-effective over time

We worked with @deeplearningai.bsky.social to create a new course called "Semantic Caching for AI Agents." Redis experts will help you build a semantic cache that makes AI agents faster and more cost-effective by recognizing when different questions mean the same thing.

AI agents often make redundant API calls for questions that mean the same thing. Semantic caching helps your agents recognize when different queries share the same meaning, reducing costs and speeding up responses.

Semantic routing improves predictability and efficiency in AI systems. RedisVL classifies user queries without LLM calls, reducing token usage and latency. Combined with LangGraph, it creates a deterministic flow for routing, execution, and decision logic. Read how here: medium.com/@bhavana0405...

medium.comWhy You Need Semantic Routing in Your LangGraph Toolkit: A Beginner’s GuideNot every question needs a 175-billion-parameter LLM. Semantic routing helps decide which model, tool, or path should handle each query

Redis reposted

🧵 1/ LLMs are stateless. They don’t remember past interactions. Every prompt is treated as an isolated request. To build actual agents, we need memory. Here’s how to do it using Spring AI and Redis — short-term + long-term memory, fully integrated. (@redis.io)

Redis reposted

1/🤔 Have you ever heard of the Count-min Sketch data structure? We just added full support for it in Redis OM Spring — and it fits right in alongside other probabilistic data structures like Bloom and Cuckoo filters. Quick rundown 👇 cc @redis.io

Redis reposted

1/4 Every time I present the same talk, it gets better. Sometimes because I spot things to improve. Sometimes because of great feedback from the audience. Check it out 🧵 cc @redis.io #javabubble

Redis reposted

Good news, everyone.

Redis@redis.io

It's a big day for us – 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. Read more here: redis.io/blog/redis-8...

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▶️ 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

There's a ton of new stuff in Redis 8, including: ➡️ The addition of the AGPLv3 open source license ➡️ Redis Stack included – no separate download ➡️ New data structures, including vector sets, JSON, time series, and probabilistic data structures like Bloom and Cuckoo filters

➡️ Redis Query Engine for advanced search ➡️ Significant performance improvements: an 87% reduction in command latency, 2x more ops per second throughput via multithreading, 35% less memory use for replication, 16x more query processing power with horizontal & vertical scaling

Redis reposted

Redis reposted

I recently joined my long-time friend @jtowermi.bsky.social on the Blue Blazes podcast to talk all things @redis.io—how it works, why it's awesome, and how devs can speed up their apps with it. J. loves Redis and, frankly, I think he just wanted to pick my brain. 🧠

Redis reposted

Redis reposted

Say you need to develop a solution that keeps a counter for unique elements. Your task is to choose a technology and/or an implementation pattern to make this happen. You are expected to store 100M elements, each 512KB in size. 🧵