Pick a catalog so Spark and Trino can query the same lakehouse table

Analytics wants to query the new table in Trino, the pipeline team already writes it with Spark, and both need to see the same data.

IntermediateRead 7 minDoing: a couple of hours7 steps

▶ Start

What you'll have at the end

One catalog wired into both engines, checked by writing a row from one and reading it back from the other

Before you start

You need

An Iceberg table already landing in shared object storage, written by a working Spark setup, plus a Trino installation that isn't pointed at that table yet.

Not covered

Deploying or operating the catalog service itself, its uptime, backups, or access policy: this recipe decides which kind of catalog fits and wires two engines to one, not how the service behind it gets run.

Leans on

7 steps

Where to go next

Set up row-level access control so two teams see different slices of one table

Once the catalog is shared, restricting which rows each team can see is the next real governance decision, separate from wiring the catalog itself.

Checked 26 Aug 2026

Part of the Data Lakehouse cookbook