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Technology · head to head

Envoy vs Trino

Envoy logo

Envoy

Technology

A high-performance L7 proxy written in C++ that is configured by an API rather than a config file, and is usually deployed under a control plane.

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: Envoy the configuration surface is very large and hand-written bootstrap YAML runs to hundreds of lines for routing that Nginx expresses in twenty, which is why nearly every production deployment sits under a control plane and inherits that control plane's constraints as well.; 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: Envoy covers xDS dynamic configuration, Trino covers Federated querying.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Envoy and Trino actually diverge.

Attributes where Envoy and Trino differ
AttributeEnvoyTrino

Identical on both: starting price (Free), pricing model (open-source), free tier (Yes), platforms (Web), 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 Envoy

  • xDS dynamic configuration
  • Protocol breadth
  • Filter chain architecture
  • Observability by default
  • Outlier detection
  • Traffic shaping
  • mTLS termination and origination
  • Hot restart

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.

Envoy

  • Acting as the data plane under a service mesh or Gateway API implementation, which is how the overwhelming majority of deployments use itnot Trino
  • An edge or API gateway that needs per-route retry budgets, circuit breaking and outlier detection rather than round-robin proxyingnot Trino
  • Migrating traffic between service versions or between a monolith and its replacement, using weighted splits and shadow trafficnot Trino
  • Standardising observability across a polyglot estate, so that latency, error rates and tracing look the same regardless of the language a service is written innot Trino

Trino

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

Where each one falls short

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

Envoy

  • The configuration surface is very large and hand-written bootstrap YAML runs to hundreds of lines for routing that Nginx expresses in twenty, which is why nearly every production deployment sits under a control plane and inherits that control plane's constraints as well.
  • xDS is the real API and it is not stable in the comfortable sense; the v2 API set was removed outright, resource types continue to be deprecated, and your control plane and Envoy binaries have to be upgraded roughly in step or the proxies stop accepting configuration.
  • Extending it properly means writing a C++ filter and building and maintaining your own Envoy binary; the alternatives are Lua, which adds per-request overhead, and proxy-wasm, whose ABI has remained effectively experimental for years with a real performance cost.
  • At sidecar density the per-proxy memory and CPU footprint is a measurable share of cluster capacity, since thousands of workloads each carry a full proxy, and this is precisely the cost that has pushed mesh projects towards node-level or ambient architectures.
  • There is no single vendor selling support for Envoy itself; you get the community plus control-plane vendors such as Solo.io and Tetrate, so an Envoy-level production bug is your own engineers in a C++ codebase unless a support contract happens to cover it.
  • Diagnosing why a request got a particular response involves reading config dumps, the stats endpoint and the RESPONSE_FLAGS codes in access logs rather than a readable error, which is a specific skill you must hire or spend months growing.

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

Envoy

Free

No published plan breakdown. See the Envoy review.

Trino

Free

No published plan breakdown. See the Trino review.

Which should you pick?

Choose Envoy if

  • You need xds dynamic configuration.
  • You want to start without paying.
  • You also want protocol breadth.
Envoy 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 Envoy or Trino better?
Neither clearly leads. Envoy 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, Envoy or Trino?
Envoy starts at Free and Trino at Free.
Does Envoy or Trino run on more platforms?
Both run on Web, so platform support will not decide this one for you.
Can I use Envoy for free?
Both have a free tier, so you can try either at no cost before committing.
What is Envoy best used for?
Envoy is most often used for acting as the data plane under a service mesh or gateway api implementation, which is how the overwhelming majority of deployments use it, an edge or api gateway that needs per-route retry budgets, circuit breaking and outlier detection rather than round-robin proxying, migrating traffic between service versions or between a monolith and its replacement, using weighted splits and shadow traffic, standardising observability across a polyglot estate, so that latency, error rates and tracing look the same regardless of the language a service is written in. Of those, acting as the data plane under a service mesh or gateway api implementation, which is how the overwhelming majority of deployments use it and an edge or api gateway that needs per-route retry budgets, circuit breaking and outlier detection rather than round-robin proxying are not what Trino is typically brought in for.
What can Envoy do that Trino cannot?
Envoy covers xDS dynamic configuration, Protocol breadth, Filter chain architecture, Observability by default. Trino covers Federated querying, Connector architecture, Predicate and aggregation pushdown, Massively parallel execution.

Answered from the vendors’ own pages

Envoy: Should I run Envoy on its own, or under a control plane?

Almost always under one. Directly authoring xDS or static bootstrap configuration is viable for a handful of routes and becomes unmanageable beyond that. Envoy Gateway, Istio, Contour, Gloo and Consul all exist to generate that configuration for you.

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.

Envoy: How does it compare with Nginx or HAProxy?

Envoy is dynamically configured over an API and instrumented far more heavily; Nginx and HAProxy are faster to configure and lighter for straightforward reverse proxying. If you never need to change routing without a reload, Envoy is more machinery than the problem requires.

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.

Envoy: What does it cost?

Nothing to licence; it is Apache 2.0 and there is no paid edition. The cost is engineering time and, for most organisations, a commercial control plane or cloud service that packages it.

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.

Envoy: Can I write extensions without C++?

You can write Lua filters or proxy-wasm modules in Rust, Go, C++ or AssemblyScript. Both carry per-request overhead compared with a native filter, and the Wasm path has been slower to stabilise than the project originally projected.

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.

Envoy: Is it a CNCF project?

Yes, it is a graduated CNCF project licensed under Apache 2.0, which means the trademark and governance sit with the foundation rather than with Lyft or any vendor.

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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