Trino stores nothing and queries everything — Hive, Iceberg, Delta Lake, Kafka, relational databases. DbSchema connects through the Trino JDBC driver, discovers every configured catalog, and diagrams the federated estate your cluster can reach.
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Trino's connector architecture registers each source as a catalog — files on S3 through
Hive or Iceberg, dimension tables in PostgreSQL, topics in Kafka. The union of it all
exists only at query time; understanding it means walking
information_schema catalog by catalog.
DbSchema assembles the map instead: every catalog a node in the tree, every table an entity on a diagram your data platform team can share.
A desktop view over the coordinator — for engineers and for analysts who skip the CLI.
DbSchema enumerates the configured catalogs and their schemas, then renders tables and views as diagram entities — the federation, drawn.
Compose queries by picking tables and columns visually, or drag fully qualified catalog.schema.table names from the tree into the editor — then read the SQL before it runs.
Page through an Iceberg table on S3, a Delta Lake table in ADLS, or a MySQL table — filters push down to the connector, and Trino's access control decides what you see.
Multi-source architectures rarely get documented, because no single source system owns the whole picture. Export interactive HTML5 documentation of every catalog Trino reaches — diagrams, tables, columns — and give the platform one browsable reference.
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Get trino-jdbc-*.jar from the Trino release page — driver class
io.trino.jdbc.TrinoDriver — and point it at the coordinator's default port
8080: jdbc:trino://coordinator:8080/hive/default. The URL path
sets the session's default catalog and schema; omit the schema and reference tables by
three-part names instead.
Authentication follows the cluster: LDAP or file-based password, Kerberos, OAuth2/JWT, or
client certificates. For HTTPS endpoints use jdbc:trino://coordinator:443/ with
TLS enabled in the connection properties, and pass session properties such as
query_max_execution_time through the advanced settings dialog. Full reference on
the Trino JDBC driver page.
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Teams working with Trino often use these engines too. Explore dedicated guides and JDBC setup for each.