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Databases · head to head

OpenSearch vs turbopuffer

OpenSearch logo

OpenSearch

Databases

Open-source search and analytics suite forked from Elasticsearch

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 OpenSearch has a free tier, so it costs nothing to try first.
  • Each has a real cost: OpenSearch diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one; 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: OpenSearch covers OpenSearch Dashboards, turbopuffer covers Object storage architecture.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which OpenSearch and turbopuffer actually diverge.

Attributes where OpenSearch and turbopuffer differ
AttributeOpenSearchturbopuffer
Starting priceFree$16/month
Pricing modelOpen source, no licence fee; managed services billed separatelysubscription
Free tierYesNo
PlatformsLinux, Docker, Kubernetes, 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 OpenSearch

  • OpenSearch Dashboards
  • Log analytics

Only in turbopuffer

  • Object storage architecture
  • Namespaces
  • Attribute filtering
  • Documented limits
  • Configurable consistency
  • Durable writes
  • Multi-query requests
  • Deployment options

Both cover

  • Full-text search
  • Vector search

What people use each for

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

OpenSearch

  • Log and observability storage where an Apache-2.0 licence is a requirementnot turbopuffer
  • Replacing Elasticsearch after the licence change without changing architecturenot turbopuffer
  • Search plus analytics on one cluster rather than two systemsnot turbopuffer

turbopuffer

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

Where each one falls short

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

OpenSearch

  • Diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one
  • Operationally heavy in the way Elasticsearch is: cluster sizing, shard strategy and JVM tuning are ongoing work
  • Smaller ecosystem of third-party tooling than Elasticsearch, which most integrations still target first
  • Overkill for plain application search, where a dedicated search engine is far simpler

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

OpenSearch

Free
  • OpenSearchFree
    • 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 OpenSearch if

  • You need opensearch dashboards.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want log analytics.
OpenSearch review

Choose turbopuffer if

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

Questions people ask

Is OpenSearch or turbopuffer better?
Neither clearly leads. OpenSearch 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, OpenSearch or turbopuffer?
OpenSearch has a free tier; the other does not. Paid plans start at Free for OpenSearch and $16/month for turbopuffer.
Does OpenSearch or turbopuffer run on more platforms?
OpenSearch runs on Linux, Docker, Kubernetes, Self-hosted. turbopuffer runs on Web.
Can I use OpenSearch for free?
Yes. OpenSearch has a free tier, so you can try it without paying. turbopuffer starts at $16/month.
What is OpenSearch best used for?
OpenSearch is most often used for log and observability storage where an apache-2.0 licence is a requirement, replacing elasticsearch after the licence change without changing architecture, search plus analytics on one cluster rather than two systems. Of those, log and observability storage where an apache-2.0 licence is a requirement and replacing elasticsearch after the licence change without changing architecture are not what turbopuffer is typically brought in for.
What can OpenSearch do that turbopuffer cannot?
OpenSearch covers OpenSearch Dashboards, Log analytics. turbopuffer covers Object storage architecture, Namespaces, Attribute filtering, Documented limits. Both handle Full-text search, Vector search.

Answered from the vendors’ own pages

OpenSearch: Is OpenSearch free?

Yes, Apache 2.0 licensed under the Linux Foundation. Amazon OpenSearch Service is a paid managed option.

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.

OpenSearch: Why does OpenSearch exist?

Elastic moved Elasticsearch off the Apache 2.0 licence in 2021. AWS forked the last Apache-licensed version, and the project now sits under the Linux Foundation.

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.

OpenSearch: Is OpenSearch compatible with Elasticsearch?

It was at the 7.10 fork point. Both have developed independently since, so compatibility weakens with every release and should be verified for the features you use.

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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