Developer Tools · head to head
Namespace vs Trino

Namespace
Developer Tools
The dev platform for the next 100 billion commits
- From
- Free
- Free plan
- Yes

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
The short version
- Each has a real cost: Namespace developer plan is pay-as-you-go only; minimum usage unclear; 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: Namespace covers Devboxes, Trino covers Federated querying.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Namespace and Trino actually diverge.
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 Namespace
- Devboxes
- GitHub Actions runners
- Docker builds
- Cross-invocation caching
- NVMe storage
- High-speed networking
- Multiple OS support
- Bazel and Turborepo 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.
Namespace
- Providing AI coding agents with cloud-based development environmentsnot Trino
- Accelerating CI builds with faster GitHub Actions runnersnot Trino
- Distributing builds across teams with managed infrastructurenot Trino
- Scaling development velocity for monorepo organizationsnot Trino
Trino
- Ad hoc analysis that spans a data lake and one or more operational databases, without building an ingestion pipeline firstnot Namespace
- Serving a BI tool a single SQL endpoint over an estate that is actually several separate storage systemsnot Namespace
- Querying Iceberg or Delta tables on object storage interactively, as the compute layer of a lakehousenot Namespace
- Investigating whether a dataset is worth ingesting, by querying it in place before committing to a pipeline for itnot Namespace
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Namespace
- Developer plan is pay-as-you-go only; minimum usage unclear
- Team plan $100/mo is competitive but usage limits may be tight
- Devbox pricing separate at $0.004/minute could add up quickly
- Enterprise plan requires custom sales conversation
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
Namespace
Free- DeveloperFree
- Pay-as-you-go
- On-demand compute
- Docker builds
- Team$100/month
- 100,000 unit minutes
- 1,000 Docker builds
- Everything in Developer
- Business$250/month
- 250,000 unit minutes
- 2,500 Docker builds
- Everything in Team
- Enterprise$undefined/custom
- Custom compute/Docker build limits
- Audit log export
- Enterprise SSO
Trino
FreeNo published plan breakdown. See the Trino review.
Which should you pick?
Choose Namespace if
- You need devboxes.
- You want to start without paying.
- You work on Cloud, Mac, Windows, Linux.
- You also want github actions runners.
Choose Trino if
- You need federated querying.
- You want to start without paying.
- You also want connector architecture.
Questions people ask
- Is Namespace or Trino better?
- Neither clearly leads. Namespace 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, Namespace or Trino?
- Namespace starts at Free and Trino at Free.
- Does Namespace or Trino run on more platforms?
- Namespace runs on Cloud, Mac, Windows, Linux. Trino runs on Web.
- Can I use Namespace for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Namespace best used for?
- Namespace is most often used for providing ai coding agents with cloud-based development environments, accelerating ci builds with faster github actions runners, distributing builds across teams with managed infrastructure, scaling development velocity for monorepo organizations. Of those, providing ai coding agents with cloud-based development environments and accelerating ci builds with faster github actions runners are not what Trino is typically brought in for.
- What can Namespace do that Trino cannot?
- Namespace covers Devboxes, GitHub Actions runners, Docker builds, Cross-invocation caching. Trino covers Federated querying, Connector architecture, Predicate and aggregation pushdown, Massively parallel execution.
Answered from the vendors’ own pages
Namespace: How is compute usage metered on the Developer plan?
Developer plan uses pay-as-you-go billing. Devboxes bill at $0.004 per minute. Storage and caching services have separate usage-based fees. A 30-day free trial is available to test usage patterns.
SourceTrino: 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.
Namespace: What is the difference between Team and Business plans?
Team ($100/mo) includes 100,000 unit minutes and 1,000 Docker builds with email support. Business ($250/mo) includes 250,000 unit minutes, 2,500 Docker builds, and high concurrency with a dedicated Slack channel.
SourceTrino: 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.
Namespace: Can Namespace support AI coding agents?
Yes, Namespace Devboxes are specifically designed as feature-rich development environments for AI coding agents, with full tooling and performance optimization.
SourceTrino: 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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