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Developer Tools · head to head

Helm vs Trino

H

Helm

Developer Tools

The package manager for Kubernetes

From
Free
Free plan
Yes
Full reviewWebsite
Trino logo

Trino

Technology

A distributed SQL engine that queries data where it already lives, across object storage, warehouses and operational databases.

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Each has a real cost: Helm licensed under Apache License 2.0 per the project's GitHub repository (helm/helm LICENSE); as open source software it has no paid tier or vendor price to compare; Trino trino stores nothing and computes no statistics of its own, so the plan it produces is only as good as the partitioning, file sizes and table statistics on the source; a Hive table of thousands of small files or a lake with no stats produces a slow query the engine cannot improve.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Helm and Trino actually diverge.

Attributes where Helm and Trino differ
AttributeHelmTrino
CategoryDeveloper ToolsTechnology

Identical on both: starting price (Free), pricing model (open-source), free tier (Yes), platforms (Web), user rating (Not yet rated).

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 Helm

Nothing recorded that Trino does not also cover.

Only in Trino

  • Federated querying
  • Connector architecture
  • Predicate and aggregation pushdown
  • Massively parallel execution
  • Fault-tolerant execution
  • Resource groups
  • Iceberg and Delta table support
  • Standard client protocols

What people use each for

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

Helm

  • Kubernetes package manager and deployment toolnot Trino

Trino

  • Ad hoc analysis that spans a data lake and one or more operational databases, without building an ingestion pipeline firstnot Helm
  • Serving a BI tool a single SQL endpoint over an estate that is actually several separate storage systemsnot Helm
  • Querying Iceberg or Delta tables on object storage interactively, as the compute layer of a lakehousenot Helm
  • Investigating whether a dataset is worth ingesting, by querying it in place before committing to a pipeline for itnot Helm

Where each one falls short

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

Helm

  • Licensed under Apache License 2.0 per the project's GitHub repository (helm/helm LICENSE); as open source software it has no paid tier or vendor price to compare
  • Contributors must sign commits under the Developer Certificate of Origin to have them accepted, per helm.sh, a process requirement not all Kubernetes tools impose

Trino

  • Trino stores nothing and computes no statistics of its own, so the plan it produces is only as good as the partitioning, file sizes and table statistics on the source; a Hive table of thousands of small files or a lake with no stats produces a slow query the engine cannot improve.
  • Federated queries pull data out of the systems they touch, so a join between a lake table and a production Postgres can put a full table scan onto an OLTP database that other applications depend on, and the person who wrote the query will not see the incident it causes.
  • Releases come roughly every one to two weeks with no community long-term support line, and deprecations arrive quickly, so you either dedicate someone to keeping current or you buy Starburst Enterprise for a supported long-term version.
  • It is memory-based and disk spilling was deprecated in favour of fault-tolerant execution, so a query exceeding cluster memory fails outright rather than degrading; enabling fault-tolerant execution requires an external exchange store on object storage and makes queries measurably slower.
  • It is a query engine and not a warehouse: there is no built-in job scheduling, no incremental materialised view maintenance and no transformation framework, so producing curated tables still needs dbt or an equivalent layer that somebody has to own.
  • The 2020 fork split the ecosystem, so documentation, connectors, Stack Overflow answers and vendor material written before then describe PrestoDB, which is now a different project with different behaviour, and following the wrong one wastes real time.

Pricing, plan by plan

Helm

Free

No published plan breakdown. See the Helm review.

Trino

Free

No published plan breakdown. See the Trino review.

Which should you pick?

Choose Helm if

  • You want to start without paying.
Helm review

Choose Trino if

  • You need federated querying.
  • You want to start without paying.
  • You also want connector architecture.
Trino review

Questions people ask

Is Helm or Trino better?
Neither clearly leads. Helm starts at Free and Trino at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Helm or Trino?
Helm starts at Free and Trino at Free.
Does Helm or Trino run on more platforms?
Both run on Web, so platform support will not decide this one for you.
Can I use Helm for free?
Both have a free tier, so you can try either at no cost before committing.
What is Helm best used for?
Helm is most often used for kubernetes package manager and deployment tool. Of those, kubernetes package manager and deployment tool is not what Trino is typically brought in for.
What can Helm do that Trino cannot?
Trino covers Federated querying, Connector architecture, Predicate and aggregation pushdown, Massively parallel execution.

Answered from the vendors’ own pages

Helm: How much does Helm cost?

Helm is free and open-source. It is a graduated project in the Cloud Native Computing Foundation (CNCF) with no commercial pricing model.

Source
Trino: What is the difference between Trino and Presto?

They share an origin. The original creators left Meta and renamed their fork from PrestoSQL to Trino in December 2020; PrestoDB continues separately under the Linux Foundation. They have diverged in features, connectors and SQL behaviour, so material written for one may not apply to the other.

Trino: Does Trino replace my data warehouse?

Not on its own. It is compute without storage, scheduling or transformation. Paired with Iceberg or Delta on object storage and something like dbt for modelling it can serve as a lakehouse; used alone it is a query layer over what you already have.

Trino: Why is my federated query slow?

Usually because a connector could not push a filter or aggregation down, so Trino is pulling whole tables across the network to join them itself. The fix is usually better source-side partitioning or statistics, or ingesting that source rather than federating it.

Trino: What happens when a query runs out of memory?

It fails. Disk spilling was deprecated in favour of fault-tolerant execution, which checkpoints to an external exchange store such as S3 and lets long queries survive memory pressure and worker loss, at the cost of noticeably slower execution.

Trino: Is there commercial support?

Yes, from Starburst, which offers Starburst Enterprise with long-term supported releases and Starburst Galaxy as a managed service. The open source project itself has no long-term support line.

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