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Databases · head to head

ArangoDB vs turbopuffer

ArangoDB logo

ArangoDB

Databases

Multi-model database for graph, document, and search

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 ArangoDB has a free tier, so it costs nothing to try first.
  • Each has a real cost: ArangoDB the company has repositioned around a wider platform, so ArangoDB is now described as the foundation inside Arango rather than the product itself; 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: ArangoDB covers Multi-model Support, turbopuffer covers Object storage architecture.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which ArangoDB and turbopuffer actually diverge.

Attributes where ArangoDB and turbopuffer differ
AttributeArangoDBturbopuffer
Starting priceFree$16/month
Pricing modelfreemiumsubscription
Free tierYesNo
PlatformsLinux, Windows, Mac, Docker, WebWeb
Founded2014Unknown

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 ArangoDB

  • Multi-model Support
  • AQL Query Language
  • Graph Traversals
  • Full-text Search
  • ACID Transactions
  • SmartGraphs
  • Satellite Collections
  • Foxx Microservices

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.

ArangoDB

  • Graph, document and key-value data in one databasenot turbopuffer
  • Vector and full-text search alongside graph traversalnot turbopuffer
  • Avoiding separate stores for related and unstructured datanot turbopuffer
  • Backing AI applications needing both graph context and vectorsnot turbopuffer

turbopuffer

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

Where each one falls short

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

ArangoDB

  • The company has repositioned around a wider platform, so ArangoDB is now described as the foundation inside Arango rather than the product itself
  • Neither the community licence terms nor cloud pricing are stated on the main site
  • arangodb.com redirects to arango.ai

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

ArangoDB

Free
  • CommunityFree
    • All data models
    • AQL queries
    • Full-text search
  • ArangoGraph$99/month
    • Managed service
    • Graph analytics
    • Enterprise support

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 ArangoDB if

  • You need multi-model support.
  • You want to start without paying.
  • You work on Linux, Windows, Mac, Docker, Web.
  • You also want aql query language.
ArangoDB review

Choose turbopuffer if

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

Questions people ask

Is ArangoDB or turbopuffer better?
Neither clearly leads. ArangoDB 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, ArangoDB or turbopuffer?
ArangoDB has a free tier; the other does not. Paid plans start at Free for ArangoDB and $16/month for turbopuffer.
Does ArangoDB or turbopuffer run on more platforms?
ArangoDB runs on Linux, Windows, Mac, Docker, Web. turbopuffer runs on Web.
Can I use ArangoDB for free?
Yes. ArangoDB has a free tier, so you can try it without paying. turbopuffer starts at $16/month.
What is ArangoDB best used for?
ArangoDB is most often used for graph, document and key-value data in one database, vector and full-text search alongside graph traversal, avoiding separate stores for related and unstructured data, backing ai applications needing both graph context and vectors. Of those, graph, document and key-value data in one database and vector and full-text search alongside graph traversal are not what turbopuffer is typically brought in for.
What can ArangoDB do that turbopuffer cannot?
ArangoDB covers Multi-model Support, AQL Query Language, Graph Traversals, Full-text Search. turbopuffer covers Object storage architecture, Namespaces, Vector search, Full-text search.

Answered from the vendors’ own pages

ArangoDB: How is ArangoDB priced?

ArangoDB offers Community Edition (free) and Enterprise Edition. Pricing is customized based on deployment model (self-managed, managed cloud AWS/GCP, or OEM/embedded) and customer requirements. Contact Arango for a quote.

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.

ArangoDB: What deployment options does ArangoDB offer?

ArangoDB can be deployed self-managed on customer infrastructure, as managed cloud (Arango Managed Platform on AWS/GCP), or as OEM/embedded solutions.

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.

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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