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Databases · head to head

Elasticsearch vs turbopuffer

Elasticsearch logo

Elasticsearch

Databases

The heart of the Elastic Stack for search and analytics

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 Elasticsearch has a free tier, so it costs nothing to try first.
  • Each has a real cost: Elasticsearch eventual consistency model with 1-second default refresh interval, not suitable for real-time transactional requirements; 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: Elasticsearch covers Full-text Search, turbopuffer covers Object storage architecture.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Elasticsearch and turbopuffer actually diverge.

Attributes where Elasticsearch and turbopuffer differ
AttributeElasticsearchturbopuffer
Starting priceFree$16/month
Pricing modelUnknownsubscription
Free tierYesNo
PlatformsLinux, Windows, macOS, Docker, KubernetesWeb
Founded2010Unknown

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 Elasticsearch

  • Full-text Search
  • Real-time Analytics
  • Distributed Architecture
  • RESTful API
  • Schema-free JSON
  • Aggregations
  • Machine Learning
  • Kibana

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.

Elasticsearch

  • Real-time applicationsnot turbopuffer
  • Content managementnot turbopuffer
  • User profilesnot turbopuffer
  • Mobile backendsnot turbopuffer
  • Cachingnot turbopuffer

turbopuffer

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

Where each one falls short

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

Elasticsearch

  • Eventual consistency model with 1-second default refresh interval, not suitable for real-time transactional requirements
  • No support for ACID transactions or rollbacks; updates delete and re-insert documents
  • JVM-dependent architecture requires careful memory management and monitoring to prevent garbage collection issues at scale

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

Elasticsearch

Free
  • Self-ManagedFree
    • Open source
    • Self-hosted
  • Elasticsearch Cloud$16.4/month
    • Managed service
    • 14-day free trial

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 Elasticsearch if

  • You need full-text search.
  • You want to start without paying.
  • You work on Linux, Windows, macOS, Docker, Kubernetes.
  • You also want real-time analytics.
Elasticsearch review

Choose turbopuffer if

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

Questions people ask

Is Elasticsearch or turbopuffer better?
Neither clearly leads. Elasticsearch 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, Elasticsearch or turbopuffer?
Elasticsearch has a free tier; the other does not. Paid plans start at Free for Elasticsearch and $16/month for turbopuffer.
Does Elasticsearch or turbopuffer run on more platforms?
Elasticsearch runs on Linux, Windows, macOS, Docker, Kubernetes. turbopuffer runs on Web.
Can I use Elasticsearch for free?
Yes. Elasticsearch has a free tier, so you can try it without paying. turbopuffer starts at $16/month.
What is Elasticsearch best used for?
Elasticsearch is most often used for real-time applications, content management, user profiles, mobile backends. Of those, real-time applications and content management are not what turbopuffer is typically brought in for.
What can Elasticsearch do that turbopuffer cannot?
Elasticsearch covers Full-text Search, Real-time Analytics, Distributed Architecture, RESTful API. turbopuffer covers Object storage architecture, Namespaces, Vector search, Full-text search.

Answered from the vendors’ own pages

Elasticsearch: Is Elasticsearch free?

Yes, Elasticsearch can be deployed as free and open-source software for self-managed installations. Elastic Cloud managed service starts at $16.40 per month, with a free 14-day trial available.

Source
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.

Elasticsearch: Can I use Elasticsearch without Kibana?

Yes, Elasticsearch is a search engine independent of Kibana. Kibana is a visualization and analytics tool that works with Elasticsearch but is optional. You can use the Elasticsearch API directly for searching.

Source
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.

Elasticsearch: Does Elasticsearch support real-time indexing?

Elasticsearch indexes data with a refresh interval, typically 1 second. Data becomes searchable after the refresh cycle, making it near-real-time but not instantaneous. This can be configured but impacts performance.

Source
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.

Elasticsearch: What are Elasticsearch's scaling limitations?

Elasticsearch requires careful operational management at scale, including shard balancing, heap sizing, and monitoring. Large clusters can suffer from garbage collection issues and become expensive to operate.

Source
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.

Elasticsearch: Does Elasticsearch support transactions and rollbacks?

No, Elasticsearch does not support ACID transactions or rollbacks. Updates are expensive operations that delete and re-insert documents, making it unsuitable for transactional workloads.

Source
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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