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Developer Tools · head to head

Cortex vs Trino

Cortex logo

Cortex

Developer Tools

Internal developer portal that scores service ownership and maturity rather than just cataloguing services

From
On request
Free plan
No
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

  • Only Trino has a free tier, so it costs nothing to try first.
  • Each has a real cost: Cortex pricing is quote only, so a platform team cannot build a business case or compare against the true cost of self-hosted Backstage without entering a sales cycle first.; 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.
  • They diverge on capability: Cortex covers Service catalogue, Trino covers Federated querying.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Cortex and Trino actually diverge.

Attributes where Cortex and Trino differ
AttributeCortexTrino
Starting priceOn requestFree
Pricing modelquoteopen-source
Free tierNoYes
PlatformsWeb, APIWeb
CategoryDeveloper ToolsTechnology

Identical on both: 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 Cortex

  • Service catalogue
  • Scorecards
  • Initiatives
  • Self-service templates
  • Query language
  • Eng intelligence
  • Integrations layer
  • On-call and ownership mapping

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.

Cortex

  • A platform team that needs to prove to leadership how far a Kubernetes or framework migration has actually progressed across hundreds of servicesnot Trino
  • An organisation where ownership of production services is genuinely unknown after reorganisations or acquisitionsnot Trino
  • Enforcing production readiness standards on new services at creation time rather than at incident reviewnot Trino
  • Replacing a self-hosted Backstage that is consuming a full-time engineer or two just to stay upgradednot Trino

Trino

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

Where each one falls short

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

Cortex

  • Pricing is quote only, so a platform team cannot build a business case or compare against the true cost of self-hosted Backstage without entering a sales cycle first.
  • The catalogue is only as accurate as the metadata you supply, so an organisation with inconsistent repository conventions spends its first quarter cleaning data before any scorecard means anything.
  • Scorecards create political friction: publishing a per-team grade turns an engineering standard into a performance metric, and teams will game the rules rather than fix the underlying issue.
  • It is closed source and hosted, so organisations with strict data residency or air-gap requirements have limited options compared with running Backstage themselves.
  • Value scales with organisation size, so a company with fifty engineers and thirty services will find the catalogue tells them nothing they did not already know while still paying an enterprise contract.

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

Cortex

On request
  • Cortex$undefined/year
    • Service catalogue and ownership mapping
    • Scorecards and initiatives
    • Self-service templates

Trino

Free

No published plan breakdown. See the Trino review.

Which should you pick?

Choose Cortex if

  • You need service catalogue.
  • You work on Web, API.
  • You also want scorecards.
Cortex 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 Cortex or Trino better?
Neither clearly leads. Cortex starts at On request and Trino at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Cortex or Trino?
Trino has a free tier; the other does not. Paid plans start at On request for Cortex and Free for Trino.
Does Cortex or Trino run on more platforms?
Cortex runs on Web, API. Trino runs on Web.
Can I use Trino for free?
Yes. Trino has a free tier, so you can try it without paying. Cortex starts at On request.
What is Cortex best used for?
Cortex is most often used for a platform team that needs to prove to leadership how far a kubernetes or framework migration has actually progressed across hundreds of services, an organisation where ownership of production services is genuinely unknown after reorganisations or acquisitions, enforcing production readiness standards on new services at creation time rather than at incident review, replacing a self-hosted backstage that is consuming a full-time engineer or two just to stay upgraded. Of those, a platform team that needs to prove to leadership how far a kubernetes or framework migration has actually progressed across hundreds of services and an organisation where ownership of production services is genuinely unknown after reorganisations or acquisitions are not what Trino is typically brought in for.
What can Cortex do that Trino cannot?
Cortex covers Service catalogue, Scorecards, Initiatives, Self-service templates. Trino covers Federated querying, Connector architecture, Predicate and aggregation pushdown, Massively parallel execution.

Answered from the vendors’ own pages

Cortex: How is Cortex different from Backstage?

Backstage is an open source framework you build and staff. Cortex is a hosted product with scorecards and initiatives out of the box and no platform team required to keep it running.

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.

Cortex: Is pricing published?

No. Cortex requires a sales conversation and prepares a custom proposal.

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.

Cortex: Can it self-host?

It is offered as a hosted product; on-premise arrangements are handled through sales rather than published.

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.

Cortex: What is the main adoption risk?

Bad or missing service metadata. The catalogue and every scorecard on top of it inherit whatever quality your repositories already have.

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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