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Developer Tools · head to head

Jitsu vs Trino

Jitsu logo

Jitsu

Developer Tools

Open source event pipeline that streams behavioural data to your own warehouse

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: Jitsu jitsu is a pipeline, not a customer data platform, so identity resolution, audience building and reverse ETL are absent and a marketing team expecting Segment parity will be disappointed.; 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: Jitsu covers Event collection, Trino covers Federated querying.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Jitsu and Trino actually diverge.

Attributes where Jitsu and Trino differ
AttributeJitsuTrino
Pricing modelPer month by event volumeopen-source
PlatformsWeb, Linux, Docker, Kubernetes, iOS, AndroidWeb
CategoryDeveloper ToolsTechnology

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 Jitsu

  • Event collection
  • Warehouse destinations
  • Connector syncs
  • Transformations
  • Bundled ClickHouse
  • Event debugger
  • Self-hosting
  • Custom domains

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.

Jitsu

  • A team paying five figures a year to a customer data platform when all it actually does is send events to Snowflakenot Trino
  • An engineering group that needs event collection running inside its own VPC for data residency or security review reasonsnot Trino
  • A product analytics setup that wants raw events in the warehouse as the source of truth rather than trapped in a vendor toolnot Trino
  • A startup that needs first-party event collection on its own domain to reduce loss from tracker blocking without paying CDP pricesnot Trino

Trino

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

Where each one falls short

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

Jitsu

  • Jitsu is a pipeline, not a customer data platform, so identity resolution, audience building and reverse ETL are absent and a marketing team expecting Segment parity will be disappointed.
  • Connector sync frequency is deliberately tiered, with the free plan limited to manual runs and one daily sync, so anything approaching operational freshness requires the paid plan or self-hosting.
  • Self-hosting means you own the reliability of a system that drops data silently when misconfigured, and event loss is uniquely hard to notice because nothing errors, the numbers are just quietly lower.
  • The connector catalogue is far smaller than Fivetran or Airbyte, so if your requirement is pulling from many SaaS sources rather than pushing events, Jitsu is the wrong half of the problem.
  • It is a small company with a small commercial team, so enterprise procurement processes around security review, contractual SLAs and support escalation take longer than with an incumbent vendor.

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

Jitsu

Free
  • Open SourceFree
    • MIT licence
    • Self-host on any cloud
    • No usage limits
  • Cloud FreeFree
    • Unlimited captured events
    • 200,000 active events per month
    • Manual connector runs only
  • Business$99/month
    • 2,000,000 active events per month
    • $40 per additional million events
    • Hourly connector sync frequency
  • Enterprise$undefined/year
    • Custom event volume
    • One minute sync frequency
    • Unlimited active syncs

Trino

Free

No published plan breakdown. See the Trino review.

Which should you pick?

Choose Jitsu if

  • You need event collection.
  • You want to start without paying.
  • You work on Web, Linux, Docker, Kubernetes, iOS, Android.
  • You also want warehouse destinations.
Jitsu 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 Jitsu or Trino better?
Neither clearly leads. Jitsu 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, Jitsu or Trino?
Jitsu starts at Free and Trino at Free.
Does Jitsu or Trino run on more platforms?
Jitsu runs on Web, Linux, Docker, Kubernetes, iOS, Android. Trino runs on Web.
Can I use Jitsu for free?
Both have a free tier, so you can try either at no cost before committing.
What is Jitsu best used for?
Jitsu is most often used for a team paying five figures a year to a customer data platform when all it actually does is send events to snowflake, an engineering group that needs event collection running inside its own vpc for data residency or security review reasons, a product analytics setup that wants raw events in the warehouse as the source of truth rather than trapped in a vendor tool, a startup that needs first-party event collection on its own domain to reduce loss from tracker blocking without paying cdp prices. Of those, a team paying five figures a year to a customer data platform when all it actually does is send events to snowflake and an engineering group that needs event collection running inside its own vpc for data residency or security review reasons are not what Trino is typically brought in for.
What can Jitsu do that Trino cannot?
Jitsu covers Event collection, Warehouse destinations, Connector syncs, Transformations. Trino covers Federated querying, Connector architecture, Predicate and aggregation pushdown, Massively parallel execution.

Answered from the vendors’ own pages

Jitsu: Is Jitsu the same as Jitsi?

No. Jitsu is an open source event data pipeline. Jitsi is an unrelated video conferencing project.

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.

Jitsu: Can I self-host for free?

Yes. The project is MIT licensed with no usage limits when self-hosted.

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.

Jitsu: How does the cost compare with Segment?

The Business plan is 99 US dollars a month for two million active events, where a per-tracked-user CDP typically costs orders of magnitude more at comparable volume.

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.

Jitsu: Does Jitsu do identity resolution?

No. It transports and transforms events; identity stitching and audiences are not part of the product.

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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