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Technology · head to head

Greenhouse vs Trino

Greenhouse logo

Greenhouse

Technology

Hiring software for growing companies

From
On request
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

  • Only Trino has a free tier, so it costs nothing to try first.
  • Each has a real cost: Greenhouse core plan lacks talent discovery and contact lookups; 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: Greenhouse covers Applicant tracking, Trino covers Federated querying.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Greenhouse and Trino actually diverge.

Attributes where Greenhouse and Trino differ
AttributeGreenhouseTrino
Starting priceOn requestFree
Pricing modelquoteopen-source
Free tierNoYes
PlatformsWeb, Ios, Android, ApiWeb
Founded2012Unknown

Identical on both: 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 Greenhouse

  • Applicant tracking
  • Interview scheduling
  • Scorecard system
  • Job board posting
  • Candidate CRM
  • Reporting & analytics
  • Offer management
  • EEO compliance

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.

Greenhouse

  • Enterprise hiring and recruiting automationnot Trino
  • Multi-location and multi-team talent acquisitionnot Trino
  • Structured interview process managementnot Trino

Trino

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

Where each one falls short

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

Greenhouse

  • Core plan lacks talent discovery and contact lookups
  • Core plan lacks email automation and applicant texting
  • Plus plan lacks resume anonymisation and application limits
  • Plus plan lacks audit logging and developer tools
  • Pricing customised by hiring volume and company size, not published
  • Only Pro tier offers audit logs and developer sandbox

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

Greenhouse

On request

No published plan breakdown. See the Greenhouse review.

Trino

Free

No published plan breakdown. See the Trino review.

Which should you pick?

Choose Greenhouse if

  • You need applicant tracking.
  • You work on Web, Ios, Android, Api.
  • You also want interview scheduling.
Greenhouse 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 Greenhouse or Trino better?
Neither clearly leads. Greenhouse 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, Greenhouse or Trino?
Trino has a free tier; the other does not. Paid plans start at On request for Greenhouse and Free for Trino.
Does Greenhouse or Trino run on more platforms?
Greenhouse runs on Web, Ios, Android, Api. Trino runs on Web.
Can I use Trino for free?
Yes. Trino has a free tier, so you can try it without paying. Greenhouse starts at On request.
What is Greenhouse best used for?
Greenhouse is most often used for enterprise hiring and recruiting automation, multi-location and multi-team talent acquisition, structured interview process management. Of those, enterprise hiring and recruiting automation and multi-location and multi-team talent acquisition are not what Trino is typically brought in for.
What can Greenhouse do that Trino cannot?
Greenhouse covers Applicant tracking, Interview scheduling, Scorecard system, Job board posting. Trino covers Federated querying, Connector architecture, Predicate and aggregation pushdown, Massively parallel execution.

Answered from the vendors’ own pages

Greenhouse: How much does Greenhouse cost?

Greenhouse does not publish specific pricing. The company states that pricing is customized based on your hiring needs, hiring volume, organizational complexity, and required features.

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.

Greenhouse: What are the Greenhouse pricing tiers?

Greenhouse offers three plan levels: Core (basic hiring structure), Plus (multi-location optimization), and Pro (complex enterprise hiring). Exact pricing requires contacting Greenhouse for a custom quote.

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.

Greenhouse: Do all Greenhouse tiers include the same features?

No. Core includes sourcing and scheduling, Plus adds automation and texting, and Pro adds enterprise data configuration and audit logs. All tiers can be customized.

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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