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Dagger vs turbopuffer

Dagger logo

Dagger

Developer Tools

Programmable CI/CD engine that runs your pipeline as containers on any runner

From
Free
Free plan
Yes
Visit DaggerFull review
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
Free plan
No
Visit turbopufferFull review

The short version

  • Dagger has a free plan, then $50/mo; turbopuffer starts at $16/mo.
  • Only Dagger lists pipelines as code; only turbopuffer lists object storage architecture.
  • Prices and features on this page were last checked on 13 November 2026.

Where they differ

Only the attributes on which Dagger and turbopuffer actually diverge.

Attributes where Dagger and turbopuffer differ
AttributeDaggerturbopuffer
Starting priceFree$16/month
Pricing modelPer month per team for Dagger CloudSubscription
Free tierYesNo
PlatformsLinux, macOS, Windows, Self-hostedWeb
CategoryDeveloper ToolsDatabases

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 Dagger

  • Pipelines as code
  • Local and CI parity
  • Content-addressed caching
  • Dagger Functions and modules
  • CI-provider agnostic
  • Dagger Cloud traces
  • GitHub Checks integration
  • Container-native execution

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.

Dagger

  • A platform team maintaining near-identical build YAML across forty repositories that wants one versioned module every repository calls insteadnot turbopuffer
  • An engineering organisation migrating off a CI provider that does not want to rewrite every pipeline as part of the migrationnot turbopuffer
  • A team whose engineers waste hours pushing commits to debug CI-only failures and needs to reproduce the exact run locallynot turbopuffer
  • A monorepo where most commits touch a small subset of services and cache-accurate step skipping cuts build minutes materiallynot turbopuffer

turbopuffer

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

Where each one falls short

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

Dagger

  • Dagger is not a CI provider, so you keep paying for GitHub Actions or GitLab runners underneath it; the Dagger Cloud subscription is an addition to your CI bill, not a replacement for it
  • Writing pipelines in Go or TypeScript raises the barrier to entry: a release engineer who could edit a YAML step now needs to read code, and the people who can fix a broken build shrink to those comfortable with the SDK
  • The engine runs as a container on the runner and needs a persistent cache volume to deliver its main benefit, so ephemeral CI runners give you correctness without the speed, and provisioning durable cache storage is extra platform work
  • The Team plan caps at ten users and ten million events per month; an organisation of any size crosses that quickly and moves to Enterprise pricing that is not published, so cost at scale is unknowable up front
  • The module ecosystem is young and thinly maintained relative to the marketplace of a mature CI provider, so integrations that exist as a one-line Action often have to be written yourself as a Dagger function

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

Dagger

Free
  • IndividualFree
    • One user
    • One million events per month
    • Workflow logs and function call traces
  • Team$50/mo
    • Up to ten users
    • Ten million events per month
    • Module insights and module catalogue
  • EnterpriseOn request
    • Custom user and event limits
    • SSO
    • Managed single-tenant deployment

turbopuffer

$16/month
  • Launch$16/mo
    • All database features
    • Multi-tenancy deployment
    • SOC2 & GDPR-ready DPA
  • Scale$256/mo
    • Everything in Launch
    • HIPAA-ready BAA
    • Single Sign-On (SSO)
  • Enterprise$4,096/mo
    • Everything in Scale
    • Single-tenancy & BYOC deployment options
    • Private networking

Which should you pick?

Choose Dagger if

  • You need pipelines as code.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Self-hosted.
  • You also want local and ci parity.
Dagger review

Choose turbopuffer if

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

Questions people ask

Is Dagger or turbopuffer better?
Neither clearly leads. Dagger 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, Dagger or turbopuffer?
Dagger has a free tier; the other does not. Paid plans start at Free for Dagger and $16/month for turbopuffer.
Does Dagger or turbopuffer run on more platforms?
Dagger runs on Linux, macOS, Windows, Self-hosted. turbopuffer runs on Web.
Can I use Dagger for free?
Yes. Dagger has a free tier, so you can try it without paying. turbopuffer starts at $16/month.
What is Dagger best used for?
Dagger is most often used for a platform team maintaining near-identical build yaml across forty repositories that wants one versioned module every repository calls instead, an engineering organisation migrating off a ci provider that does not want to rewrite every pipeline as part of the migration, a team whose engineers waste hours pushing commits to debug ci-only failures and needs to reproduce the exact run locally, a monorepo where most commits touch a small subset of services and cache-accurate step skipping cuts build minutes materially. Of those, a platform team maintaining near-identical build yaml across forty repositories that wants one versioned module every repository calls instead and an engineering organisation migrating off a ci provider that does not want to rewrite every pipeline as part of the migration are not what turbopuffer is typically brought in for.
What can Dagger do that turbopuffer cannot?
Dagger covers Pipelines as code, Local and CI parity, Content-addressed caching, Dagger Functions and modules. turbopuffer covers Object storage architecture, Namespaces, Vector search, Full-text search.

Answered from the vendors’ own pages

Dagger: Does Dagger replace GitHub Actions?

No. Dagger runs inside GitHub Actions or any other CI. It replaces the YAML that describes your pipeline steps, not the trigger and runner layer.

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.

Dagger: Is the engine open source?

Yes, the Dagger engine and SDKs are open source and free. Dagger Cloud, the observability product, is what costs money.

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.

Dagger: What is an event in the pricing?

Dagger Cloud meters pipeline telemetry events. One million per month is free; the Team plan at 50 USD per month allows ten million.

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.

Dagger: Can I run the same pipeline on my laptop?

Yes, that is the main reason teams adopt it. The dagger CLI executes the identical graph locally, so CI-only failures become reproducible.

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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