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Databases · head to head

Presto vs Trino

Presto logo

Presto

Databases

The Meta-lineage distributed SQL query engine, distinct from the Trino fork

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: Presto the original creators and most of the active contributor base left for Trino in 2020, so Presto has the smaller community, fewer connectors and slower feature delivery of the two branches.; 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: Presto covers In-memory execution, Trino covers Connector architecture.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Presto and Trino actually diverge.

Attributes where Presto and Trino differ
AttributePrestoTrino
Pricing modelOpen source, no licence feeopen-source
PlatformsLinux, Docker, KubernetesWeb
CategoryDatabasesTechnology

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 Presto

  • In-memory execution
  • Open table format support
  • Presto C++ workers
  • ANSI SQL
  • Pluggable connectors

Only in Trino

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

Both cover

  • Federated querying

What people use each for

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

Presto

  • An existing PrestoDB estate that needs continued upgrades rather than a migration to Trinonot Trino
  • A team buying IBM watsonx.data, where Presto is the underlying query enginenot Trino
  • Joining a Hive or Iceberg lake to an operational PostgreSQL database in one query without an ETL stepnot Trino
  • Very large scale interactive SQL where the Meta-tested branch is a specific requirementnot Trino

Trino

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

Where each one falls short

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

Presto

  • The original creators and most of the active contributor base left for Trino in 2020, so Presto has the smaller community, fewer connectors and slower feature delivery of the two branches.
  • Documentation, tutorials and Stack Overflow answers for the two projects are frequently mixed up, and a solution written for Trino often does not apply, which costs real debugging time.
  • It is a query engine with no storage of its own, so query performance is dictated by your file layout, partitioning and statistics, and a badly organised lake makes Presto look slow.
  • Memory-bound execution means a single large join can fail the whole query rather than spilling gracefully, and tuning cluster memory settings is a persistent operational chore.
  • Commercial support has consolidated into IBM since the Ahana acquisition, so the independent vendor market that once existed around Presto is largely gone.

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

Presto

Free
  • PrestoFree
    • Apache 2.0 licence
    • Presto Foundation governance under the Linux Foundation
    • No node or query limits

Trino

Free

No published plan breakdown. See the Trino review.

Which should you pick?

Choose Presto if

  • You need in-memory execution.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes.
  • You also want open table format support.
Presto review

Choose Trino if

  • You need connector architecture.
  • You want to start without paying.
  • You also want predicate and aggregation pushdown.
Trino review

Questions people ask

Is Presto or Trino better?
Neither clearly leads. Presto 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, Presto or Trino?
Presto starts at Free and Trino at Free.
Does Presto or Trino run on more platforms?
Presto runs on Linux, Docker, Kubernetes. Trino runs on Web.
Can I use Presto for free?
Both have a free tier, so you can try either at no cost before committing.
What is Presto best used for?
Presto is most often used for an existing prestodb estate that needs continued upgrades rather than a migration to trino, a team buying ibm watsonx.data, where presto is the underlying query engine, joining a hive or iceberg lake to an operational postgresql database in one query without an etl step, very large scale interactive sql where the meta-tested branch is a specific requirement. Of those, an existing prestodb estate that needs continued upgrades rather than a migration to trino and a team buying ibm watsonx.data, where presto is the underlying query engine are not what Trino is typically brought in for.
What can Presto do that Trino cannot?
Presto covers In-memory execution, Open table format support, Presto C++ workers, ANSI SQL. Trino covers Connector architecture, Predicate and aggregation pushdown, Massively parallel execution, Fault-tolerant execution. Both handle Federated querying.

Answered from the vendors’ own pages

Presto: Is this Presto or Trino?

This is PrestoDB, the branch that stayed at Facebook and moved to the Linux Foundation. Trino is the 2020 fork by the original creators.

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.

Presto: Which should I choose for a new project?

Trino, in most cases. It has the larger community, more connectors and more commercial options.

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.

Presto: Who maintains Presto now?

Principally Meta, Uber and IBM, which acquired the Presto vendor Ahana in 2023.

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.

Presto: Is it still actively released?

Yes, releases continue on a regular cadence under the Presto Foundation.

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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