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Databases · head to head

Memcached vs turbopuffer

M

Memcached

Databases

Distributed memory object caching system

From
Free
Rated
-
Full reviewWebsite
turbopuffer logo

turbopuffer

Databases

Closed-source vector and full-text search service built directly on object storage, with cold queries measured in seconds rather than milliseconds.

From
$16/month
Rated
-
Full reviewWebsite

The short version

  • Only Memcached has a free tier, so it costs nothing to try first.
  • Each has a real cost: Memcached no persistence at all: restart a node and its cache is gone, which every design must assume; turbopuffer a cold namespace pays object storage latency on the first query, with a documented p90 around 1,214 ms on a million documents, so any interactive search box needs the data kept warm or the user waits about a second.
  • They diverge on capability: Memcached covers In-memory key-value cache, turbopuffer covers Object storage architecture.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Memcached and turbopuffer actually diverge.

Attributes where Memcached and turbopuffer differ
AttributeMemcachedturbopuffer
Starting priceFree$16/month
Pricing modelOpen source, no licence fee; managed cloud billed separatelysubscription
Free tierYesNo
PlatformsLinux, macOS, Windows, Docker, Self-hostedWeb

Identical on both: user rating (Not yet rated), category (Databases).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Memcached

  • In-memory key-value cache
  • Multithreaded
  • Client-side sharding
  • Predictable memory use

Only in turbopuffer

  • Object storage architecture
  • Namespaces
  • Vector search
  • Full-text search
  • Attribute filtering
  • Documented limits
  • Configurable consistency
  • Durable writes

What people use each for

The jobs each tool is most often brought in to do.

Memcached

  • Caching expensive database query results to cut loadnot turbopuffer
  • Session storage where losing sessions on restart is acceptablenot turbopuffer
  • Fronting an API whose responses are costly and change slowlynot turbopuffer

turbopuffer

  • A product with one search index per customer and thousands of customers, most of whose data is idle on any given daynot Memcached
  • Very large corpora where holding every vector in memory is the dominant cost and occasional cold-query latency is acceptablenot Memcached
  • Hybrid retrieval combining BM25 and vector search where running and synchronising two separate systems is the problem being solvednot Memcached
  • Retrieval for agent and assistant products where indexes are created and destroyed frequently and per-index overhead must be near zeronot Memcached

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Memcached

  • No persistence at all: restart a node and its cache is gone, which every design must assume
  • No replication or failover, so losing a node loses that share of the cache
  • Only simple key-value, with none of the lists, sorted sets or streams Redis offers
  • Values are capped at 1MB by default, which surprises teams caching large documents

turbopuffer

  • A cold namespace pays object storage latency on the first query, with a documented p90 around 1,214 ms on a million documents, so any interactive search box needs the data kept warm or the user waits about a second.
  • Queries are eventually consistent by default, and after roughly 128 MiB of outstanding writes new data is invisible until indexed, which the vendor puts at tens of seconds for small namespaces and tens of minutes for large ones, so a bulk re-index is not immediately queryable.
  • It is closed source with no community edition, so single-tenant or bring-your-own-cloud deployment is a commercial negotiation rather than a deployment choice, and there is no path to running it yourself if the relationship ends.
  • Per-namespace ceilings, roughly 10,000 writes per second, 32 MB/s and 500 million documents per shard, mean a single enormous index has to be sharded across namespaces by your application rather than by the service.
  • It is a search engine, not a database: there are no joins, no cross-document transactions and no SQL, so it sits beside a primary datastore and keeping the two in step is work that belongs to you.

Pricing, plan by plan

Memcached

Free
  • MemcachedFree
    • Full functionality
    • Self-hosted
    • No usage limits

turbopuffer

$16/month
  • Launch$16/month
    • All database features
    • Multi-tenancy deployment
    • SOC2 & GDPR-ready DPA
  • Scale$256/month
    • Everything in Launch
    • HIPAA-ready BAA
    • Single Sign-On (SSO)
  • Enterprise$4096/month
    • Everything in Scale
    • Single-tenancy & BYOC deployment options
    • Private networking

Which should you pick?

Choose Memcached if

  • You need in-memory key-value cache.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Docker, Self-hosted.
  • You also want multithreaded.
Memcached review

Choose turbopuffer if

  • You need object storage architecture.
  • You also want namespaces.
turbopuffer review

Questions people ask

Is Memcached or turbopuffer better?
Neither clearly leads. Memcached starts at Free and turbopuffer at $16/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Memcached or turbopuffer?
Memcached has a free tier; the other does not. Paid plans start at Free for Memcached and $16/month for turbopuffer.
Does Memcached or turbopuffer run on more platforms?
Memcached runs on Linux, macOS, Windows, Docker, Self-hosted. turbopuffer runs on Web.
Can I use Memcached for free?
Yes. Memcached has a free tier, so you can try it without paying. turbopuffer starts at $16/month.
What is Memcached best used for?
Memcached is most often used for caching expensive database query results to cut load, session storage where losing sessions on restart is acceptable, fronting an api whose responses are costly and change slowly. Of those, caching expensive database query results to cut load and session storage where losing sessions on restart is acceptable are not what turbopuffer is typically brought in for.
What can Memcached do that turbopuffer cannot?
Memcached covers In-memory key-value cache, Multithreaded, Client-side sharding, Predictable memory use. turbopuffer covers Object storage architecture, Namespaces, Vector search, Full-text search.

Answered from the vendors’ own pages

Memcached: Is Memcached free?

Yes, open source with no licence fee.

turbopuffer: Can I self-host turbopuffer?

There is no open source or community edition. Single-tenant and bring-your-own-cloud deployments exist as commercial arrangements, but there is no way to run it independently of the vendor.

Memcached: Memcached or Redis?

Memcached is a pure cache: simpler, multithreaded and very predictable. Redis adds persistence, replication and rich data structures, which is why it is the default choice unless you specifically want a cache and nothing more.

turbopuffer: How fast is it really?

Warm queries perform comparably to in-memory search engines. Cold queries, where data is not cached, have a documented p90 around 1,214 ms on a million documents. Write p90 is around 248 ms for a 512 KB upsert because writes go straight to object storage.

Memcached: Does Memcached persist data?

No. Everything is in memory and lost on restart, by design.

turbopuffer: Is it consistent?

Eventually consistent by default, with the vendor reporting that over 99.8% of queries return consistent data. Strong consistency can be requested per query at a latency cost. Large write bursts have a longer visibility delay while indexing catches up.

turbopuffer: What is it best at?

Large numbers of namespaces where most are idle. The architecture makes cold data cheap to keep, which is exactly the shape of a multi-tenant product with a long tail of inactive customers.

turbopuffer: What are the hard limits?

Up to 128 billion documents and 256 TB per namespace, 500 million documents per shard, 64 MiB per document, 10,752 dense vector dimensions, roughly 10,000 writes per second per namespace and a maximum result set of 10,000.

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