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Developer Tools · head to head

Refact vs Trino

Refact logo

Refact

Developer Tools

Autonomous AI coding agent for development tasks

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: Refact requires configuration for optimal performance; 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: Refact covers Autonomous agent workflows, Trino covers Federated querying.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Refact and Trino actually diverge.

Attributes where Refact and Trino differ
AttributeRefactTrino
Pricing modelFreemium with paid tiersopen-source
PlatformsVS Code, WebWeb
CategoryDeveloper ToolsTechnology
Founded2023Unknown

Identical on both: starting price (Free), free tier (Yes), 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 Refact

  • Autonomous agent workflows
  • IDE chat
  • Real-time code completions
  • GitHub integration
  • Database integration
  • On-premise deployment
  • Multi-LLM support
  • 25+ language support

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.

Refact

  • Autonomous code generation for development tasksnot Trino
  • End-to-end bug fixes and refactoringnot Trino
  • Multi-language software development accelerationnot Trino
  • Enterprise development with data privacy requirementsnot Trino

Trino

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

Where each one falls short

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

Refact

  • Requires configuration for optimal performance
  • On-premise deployment adds operational complexity
  • Free tier limited by daily agent request quota
  • Coin system adds complexity to cost calculation

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

Refact

Free
  • FreeFree
    • Limited daily agent usage
    • Unlimited completions
    • 2,000 coins for agent and chat
  • Pro$10/month
    • 40 daily agent requests
    • 64k context window
    • 10,000 coins monthly
  • Enterprise$undefined/custom
    • On-premise deployment
    • Custom coin allocation
    • Fine-tuning support

Trino

Free

No published plan breakdown. See the Trino review.

Which should you pick?

Choose Refact if

  • You need autonomous agent workflows.
  • You want to start without paying.
  • You work on VS Code, Web.
  • You also want ide chat.
Refact 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 Refact or Trino better?
Neither clearly leads. Refact 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, Refact or Trino?
Refact starts at Free and Trino at Free.
Does Refact or Trino run on more platforms?
Refact runs on VS Code, Web. Trino runs on Web.
Can I use Refact for free?
Both have a free tier, so you can try either at no cost before committing.
What is Refact best used for?
Refact is most often used for autonomous code generation for development tasks, end-to-end bug fixes and refactoring, multi-language software development acceleration, enterprise development with data privacy requirements. Of those, autonomous code generation for development tasks and end-to-end bug fixes and refactoring are not what Trino is typically brought in for.
What can Refact do that Trino cannot?
Refact covers Autonomous agent workflows, IDE chat, Real-time code completions, GitHub integration. Trino covers Federated querying, Connector architecture, Predicate and aggregation pushdown, Massively parallel execution.

Answered from the vendors’ own pages

Refact: How many programming languages does Refact support?

Refact supports 25+ programming languages including Python, JavaScript, Go, Rust, Java, C++, and many others.

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.

Refact: Can I deploy Refact on-premises?

Yes. Refact offers on-premise deployment options for organizations requiring complete data control and privacy.

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.

Refact: What LLMs does Refact support?

Refact works with multiple LLMs including Claude, GPT-4, and open-source models, giving you flexibility in model selection.

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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