Data Panda lands operational data in Iceberg, Delta or Hive tables on S3 and points Trino at it. From there one SQL surface federates the lake, the warehouse and the source systems behind your business, so reporting, automation, AI and apps read the same numbers without an ETL hop in between.
Trino is the open-source distributed SQL query engine that grew out of Presto, the project Martin Traverso, David Phillips and Dain Sundstrom started inside Facebook in 2012 to run interactive analytics on a Hadoop warehouse the size of the company itself. The three founders left Facebook in 2018, kept building the engine outside as PrestoSQL, and renamed the project Trino in December 2020 after a trademark dispute with Facebook over the Presto name. The code stays Apache 2.0; the Trino Software Foundation governs it; Starburst, the company co-founded by the same Presto creators alongside Justin Borgman, ships the commercial managed version.
The architecture is coordinator and workers, with one SQL plan that fans out across as many machines as the cluster has. What makes Trino different from a warehouse is the connector layer: Iceberg, Delta Lake, Hudi, Hive, Postgres, MySQL, SQL Server, Snowflake, BigQuery, Cassandra, MongoDB, Kafka and roughly thirty more all sit behind the same SQL dialect, joinable in one query. That is why Netflix, LinkedIn, Goldman Sachs, Salesforce, Stripe, Shopify and Lyft built their interactive analytics on Trino: one engine reads Parquet on S3 next to Postgres rows next to Snowflake tables, without a copy step in between. Trino is not an OLTP database and not a replacement for Snowflake or BigQuery; it is the SQL layer that lets you query the lake and federate across systems without lifting the data out first.
Power BI, Tableau and Metabase read curated Iceberg or Delta tables through Trino instead of waiting for a warehouse load.
Trino joins operational databases, the warehouse and the lake in one query, so you stop copying data just to combine it.
LLM and ML pipelines pull governed Trino result sets instead of stitching CSVs together.
Custom dashboards, customer portals and Streamlit apps query Trino once and reach every backing store behind it.
A list of concrete reports, automations and AI features we have built on Trino data. Pick the one that matches your situation.
Is Trino a replacement for Snowflake or BigQuery?
No. Trino is a query engine, not a managed warehouse. It runs SQL across whatever storage the connectors point at: Iceberg or Delta on S3, Postgres, MySQL, Snowflake itself, BigQuery, Cassandra, Mongo. Snowflake and BigQuery still win when you want a managed warehouse with built-in storage, governance and concurrency for many BI users. Plenty of stacks now run both: the warehouse for the curated reporting layer, Trino for federation across the lake and the operational systems that nobody wants to copy in.
Why would we run Trino instead of Athena?
Athena is managed Trino on AWS, so for S3-only workloads inside one AWS account it is often the simpler choice. Self-managed Trino or Starburst becomes interesting when you need federation across systems Athena does not know (a Snowflake account, a Postgres replica, a MongoDB cluster), when you want to pin compute and avoid per-query billing, or when you run on Azure or GCP. The point is workload, not religion: small AWS-only team starts with Athena, federated cross-cloud setups end up on Trino or Starburst Galaxy.
We have an existing data lake on S3. What does Trino change?
It turns the lake into something analysts can query with SQL instead of Spark or notebooks. Once Iceberg or Delta tables sit on S3, a Trino cluster gives BI tools a JDBC endpoint that reads them in place with partition pruning and predicate pushdown. The same cluster can join those lake tables with Postgres or the warehouse in one query, so the lake stops being a write-only archive and starts being the analytical surface.
Finance teams keep multi-year close history on cheap object storage and still query it from the same SQL endpoint as the live ledger. A reconciliation that needs three years of journal entries no longer waits on a warehouse restore; Trino reads the Iceberg tables directly.
Sales operations gets one SQL surface that joins CRM, billing, support and product usage without a nightly ELT into a separate warehouse. Account reviews stop blocking on a data engineering ticket because the data already sits where Trino can read it.
Data and platform leads cap warehouse cost by routing exploratory and federation workloads through Trino on the lake instead of the production warehouse. Sensitive operational systems stay where they are; Trino reads them in place with role-based credentials per catalog.
You keep the reporting tool you already have. We connect it to the warehouse where your Trino data lives.
OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.
Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.
We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.
We set up the foundation. Your team builds on top.
Best fit Teams that already have a BI analyst or data engineer and want to own the build.
We build the whole thing, end to end.
Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.
You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.
Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.
No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.
Trino is the project that the original Presto founders Martin Traverso, David Phillips and Dain Sundstrom kept building after they left Facebook in 2018. They first called it PrestoSQL and renamed it to Trino in December 2020 after a trademark dispute with Facebook over the Presto name. The Apache 2.0 codebase, the contributors and the community moved across; PrestoDB, the Linux Foundation project, is the separate fork that stayed inside Facebook's orbit. When teams say 'Presto' today they usually mean Trino.
Self-managed Trino is fine for a steady, well-understood workload where one team owns the cluster lifecycle. Starburst Galaxy is the managed cloud version from the company that the Trino creators co-founded, and removes the cluster operations in exchange for a per-credit bill, plus it adds connectors, governance and a query catalog the open-source build does not ship. We size the choice on how much patience the team has for cluster ops versus how much budget there is for managed compute.
Both work and Trino has a first-class connector for each. Iceberg is the format the Trino project itself leans into hardest, with strong support for partition evolution, hidden partitioning and time travel. Delta Lake works through the Delta connector and is the natural pick for stacks that already use Databricks. The decision is rarely Trino-driven; it follows where the rest of the data platform lives.
We review your Trino setup and the systems around it. Together we pick the first thing worth building.