{"slug": "scale-your-workloads-without-paying-all-ram-prices", "title": "Scale your workloads without paying all-RAM prices", "summary": "Redis launched Redis Flex, a database that combines RAM and SSD in a single Redis instance, claiming it costs up to 80% less per gigabyte than RAM alone with no code changes. Redis said server DRAM prices roughly doubled in early 2026 as memory makers shifted capacity to high-bandwidth memory for AI accelerators, and Redis Flex lets teams choose a RAM ratio from 10% to 50% per workload, with Redis Search support for large SSD-stored indexes now in preview on Redis Cloud Pro.", "body_md": "Blog\n\n# Scale your workloads without paying all-RAM prices\n\n## AI is pushing memory prices up, fast\n\nFor decades, memory got cheaper every year. In late 2025 that reversed. Memory makers shifted capacity to the high-bandwidth memory AI accelerators need, cloud providers locked up the rest, and server DRAM prices roughly doubled in early 2026. For some teams the constraint isn't price anymore; it's getting an allocation at all.\n\nIf you run an in-memory database, this hits you directly. RAM you already own doesn't get pricier. Adding capacity, replicating it, or scaling for growth does.\n\n## Storing less isn't a real answer\n\nWhen RAM gets expensive, growth is where it hurts. Every new user, feature, or agent adds data that has to stay fast, and now every gigabyte of it costs more.\n\nSo teams scale back instead:\n\n- **Shorter history.** Fewer signals to decide with.\n- **A smaller cache.** More requests fall through to a slower database.\n- **Data pushed to other systems.** More lookups, more to maintain.\n\nEach one lowers the bill by lowering what the application can do.\n\n**Fraud and recommendation systems feel this most.** They make hundreds of thousands of decisions per second with a few milliseconds each, and every decision is only as good as the features you can afford to serve.\n\n**Agents compound it.** A single task fans out into dozens of steps, each pulling context, memory, and real-time signals. Trim any of them and the agent gets worse.\n\nThe problem isn't that data grows. It's that scaling it while maintaining real-time performance now costs more than it should, and the fixes on offer all mean settling for less. What teams need is a way to keep scaling without paying RAM prices for everything.\n\n## Grow agent data without scaling RAM costs\n\nJoin us to look at areas where this problem shows up, and how to design for them as your agentic architecture scales.\n## How tiering should work\n\nPair RAM with SSD. Hot data stays in memory; everything else lives on SSD at a fraction of the cost.\n\nBoth keys and values move to SSD, so RAM is reserved for the data your app touches constantly. When a request comes in for something on SSD, it's pulled into RAM, served, and kept there while it stays busy. Your application still sees one database and one API.\n\nHow much RAM you need depends on the workload:\n\n- **Huge dataset, small hot slice.** Runs on a low RAM share.\n- **Touches most of its data.** Needs more.\n- **Sub-millisecond on every request.** Stays all-RAM.\n\nCapacity becomes a dial you control rather than a bill you absorb.\n\n## Put this into practice\n\nDial in your RAM and SSD ratio so you can run terabyte-scale datasets without keeping everything in memory.\n## Put this into practice with Redis Flex\n\nRedis Flex combines RAM and SSD in a single Redis database. Hot data stays in RAM; less frequently used keys and values move to SSD. You choose a RAM ratio from 10% to 50% per workload and change it as your needs or memory prices change.\n\nRedis Flex costs **up to 80% less per gigabyte** than RAM alone, on the same Redis you already use, with no code changes.\n\nFlex now supports Redis Search too, with large indexes stored on SSD (in preview on Redis Cloud Pro).\n\nIf you're growing a feature store, expanding a cache, or giving your agents more to remember, Flex lets you keep more useful data while buying less of the most expensive resource in the data center.\n\n[Talk with a solutions architect](https://redis.io/ram-cost-control/) about using Redis Flex to meet your performance, scale, and cost goals.\n\n## Get started with Redis today\n\nSpeak to a Redis expert and learn more about enterprise-grade Redis today.", "url": "https://wpnews.pro/news/scale-your-workloads-without-paying-all-ram-prices", "canonical_source": "https://redis.io/blog/scale-your-workloads-without-paying-all-ram-prices/", "published_at": "2026-09-30 00:00:00+00:00", "updated_at": "2026-10-02 18:40:00.565315+00:00", "lang": "en", "topics": ["ai-infrastructure", "ai-agents", "ai-tools"], "entities": ["Redis", "Redis Flex", "Redis Search", "Redis Cloud Pro"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/scale-your-workloads-without-paying-all-ram-prices", "markdown": "https://wpnews.pro/news/scale-your-workloads-without-paying-all-ram-prices.md", "text": "https://wpnews.pro/news/scale-your-workloads-without-paying-all-ram-prices.txt", "jsonld": "https://wpnews.pro/news/scale-your-workloads-without-paying-all-ram-prices.jsonld"}}