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Productboard vs Trino

Productboard logo

Productboard

Technology

Product management system that helps you understand what customers need

From
Free
Rated
-
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
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Productboard per-maker pricing escalates quickly for larger product organizations; 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: Productboard covers Customer insights portal, Trino covers Federated querying.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Productboard and Trino actually diverge.

Attributes where Productboard and Trino differ
AttributeProductboardTrino
Pricing modelUnknownopen-source
PlatformsWeb, Mobile, APIWeb
Founded2014Unknown

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Technology).

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 Productboard

  • Customer insights portal
  • Feature prioritization
  • Dynamic roadmaps
  • User feedback management
  • Product hierarchy
  • Custom scoring
  • Release planning
  • Stakeholder alignment

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.

Productboard

  • Product roadmappingnot Trino
  • Feature prioritizationnot Trino
  • Customer feedback managementnot Trino
  • Stakeholder alignmentnot Trino
  • Product strategynot Trino

Trino

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

Where each one falls short

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

Productboard

  • Per-maker pricing escalates quickly for larger product organizations
  • Connection to Jira often functions as one-way integration with limitations
  • Manual feedback collection processes are time-consuming and error-prone
  • Lacks strategic product management functions beyond feedback centralization

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

Productboard

Free
  • StarterFree
    • 50 feedback notes
    • 1 Teamspace
    • 1 Objective
  • Spark$15/month
    • Feedback portal
    • Prioritization boards
    • Roadmap views

Trino

Free

No published plan breakdown. See the Trino review.

Which should you pick?

Choose Productboard if

  • You need customer insights portal.
  • You want to start without paying.
  • You work on Web, Mobile, API.
  • You also want feature prioritization.
Productboard 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 Productboard or Trino better?
Neither clearly leads. Productboard 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, Productboard or Trino?
Productboard starts at Free and Trino at Free.
Does Productboard or Trino run on more platforms?
Productboard runs on Web, Mobile, API. Trino runs on Web.
Can I use Productboard for free?
Both have a free tier, so you can try either at no cost before committing.
What is Productboard best used for?
Productboard is most often used for product roadmapping, feature prioritization, customer feedback management, stakeholder alignment. Of those, product roadmapping and feature prioritization are not what Trino is typically brought in for.
What can Productboard do that Trino cannot?
Productboard covers Customer insights portal, Feature prioritization, Dynamic roadmaps, User feedback management. Trino covers Federated querying, Connector architecture, Predicate and aggregation pushdown, Massively parallel execution.

Answered from the vendors’ own pages

Productboard: What is included in the Spark plan?

Productboard Spark at USD 15/maker/month (annual) or USD 19/maker/month (monthly) includes the feedback portal, prioritization boards, roadmap views, and AI features. Spark includes 250 AI credits per maker per month.

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.

Productboard: Is there a free plan available?

Yes. Productboard offers a free Starter plan with 50 feedback notes, 1 Teamspace, 1 Objective, and 1 Product Portal.

Source
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.

Productboard: How many AI credits do new users get?

New signups receive 150 free AI credits to trial AI features, plus the included 250 credits per maker per month on paid plans.

Source
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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