Search on Flex comes to Redis Cloud Pro: same Search API, a fraction of the RAM

Redis Search indexes can now live on Flex tiered storage in Redis Cloud. Large-scale search on Redis is within reach in the cloud, with no changes to your queries or your code.

Search workloads have a way of outgrowing their budget. A product catalog picks up more attributes, a fraud team wants to screen against full histories instead of samples, a RAG pipeline needs the whole corpus rather than the slice that fits in memory. Each step is reasonable on its own. Together they push an index past the point where holding every byte of it in RAM makes economic sense.

Until now, that was where Redis Search stopped. Indexes had to live entirely in memory, so at terabyte scale the math rarely worked, and many teams ran a separate search engine beside Redis instead.

Search on Flex changes that. The queries you write, the indexes you define, and the clients you connect with all stay exactly the same. What changes is where the index lives.

Built on Flex tiering

Redis Flex already manages the placement of keys and values between RAM and SSD, keeping hot data in memory and moving warm data to disk. Search on Flex extends the same approach to the search index itself.

The full index resides on Flex tiered storage, while only the hot index metadata stays in RAM. The result is an index whose memory footprint is roughly ten percent of an equivalent in-memory index. You choose the RAM-to-Flash ratio for the database, so you decide where on the price-to-performance curve your workload sits, and you can move that dial later without re-indexing or rewriting anything. Tune it to 100% RAM and you get the Redis performance you already know.

Disk reads cost latency, so Search on Flex pairs with Query Performance Factor (QPF), which spreads query execution across multiple vCPUs to deliver the throughput your workload needs. Our design target is what we call the 10:10 rule: roughly ten times in-memory query latency at roughly ten percent of the RAM footprint. For most search, retrieval, and semantic-similarity SLAs, that is a trade worth making. For workloads that were never going to fit in RAM, it is the difference between running on Redis and running somewhere else.

If you want to understand how Flex tiering works underneath, see the Redis Flex documentation. In Redis Cloud Pro, all of this is managed for you.

What this means in practice

Search at a scale that was not viable before is now. All-in-RAM economics kept most Redis Search deployments small. The workloads coming to Search on Flex are measured in terabytes, from one to the low tens. Fraud and compliance screening across complete histories, feature stores with wider and longer features, document retrieval across full catalogs and knowledge bases, and agent context retrieval over an entire corpus all become practical on Redis.

Feed AI more context than memory allows. RAG pipelines, agent context retrieval, and hybrid text-plus-vector workloads outgrow RAM fast. Search on Flex holds terabyte-scale embeddings and documents on SSD, so your retriever draws from the full corpus rather than the portion that fits in memory.

One platform instead of two. Many teams run Redis as the cache with Elasticsearch, OpenSearch, or a dedicated vector database beside it as the search layer because a Redis index at that scale did not fit in RAM. Search on Flex removes that second engine. Your source database stays the system of record; Redis becomes the cache and the search layer in one. Pair it with Redis Data Integration, which streams data from your existing databases into Redis in near real time, and the full dataset you sync becomes searchable, not just the subset you cache. One less engine to run, sync, and pay for.

Start on Flex, grow into RAM. Because the same engine and commands run on both, you can begin with a disk-heavy configuration while you are early and cost-conscious, then shift toward RAM and more QPF as demand grows. Price and performance are a setting, not a migration project. Worried about AI cost? Start on Flex.

Nothing changes in your code. Search on Flex uses the same Redis Search API. FT.CREATE, FT.SEARCH, and the client libraries you already use behave the same way. There is nothing to rewrite and no new interface to adopt.

What is available today

The Redis Cloud Pro Preview focuses on the index types that matter most for mixed search and retrieval workloads:

• HASH documents
• TEXT fields, including prefix, infix, suffix, wildcard, and fuzzy matching
• TAG fields
• VECTOR fields with HNSW and FLAT indexes
• Loading fields from the keyspace with SORTBY and RETURN
• High availability, persistence, backup, and upgrades

Redis Cloud Pro currently exposes a narrower feature set than Redis Software. NUMERIC and GEO fields, JSON documents, FT.AGGREGATE, FT.HYBRID, and background indexing are available on Redis Software today and will land on Redis Cloud Pro as the Cloud release catches up.

Full parity with in-memory Search is the goal for GA, and we are prioritizing the remaining gaps based on what customers ask for.

You pay for your Flex database as usual. There is currently no additional charge for the QPF used by Search on Flex.

Getting started

Search on Flex is now in Preview on Redis Cloud Pro. To try it, enable the opt-in Preview flag in the Redis Cloud console for your Redis Cloud Pro subscription. Once enabled, you can create Flex databases with Redis Search indexes on tiered storage. Terraform support is available at preview level. As a Preview feature, the supported feature set will continue to expand ahead of general availability.

Search should not stop at the size of RAM

The point of all this is simple. Whether you can search your data should be decided by what your application needs, not by how much of the index you can afford to hold in memory. Redis Flex already made terabyte-scale datasets practical in Redis Cloud. Search on Flex brings one of the most-used Redis capabilities along with it.

Same queries, same clients, same Redis. Indexes that finally get to be as large as your data.

Try the Search on Flex Preview on Redis Cloud Pro, or learn more about Redis Flex.