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Trino Cheat Sheet

Trino Cheat Sheet

Back to Data Engineering
Updated 2026-04-12
Next Topic: Unity Catalog in Databricks Cheat Sheet

Trino is a distributed SQL query engine designed for interactive analytics on large datasets across heterogeneous data sources. Originally created at Facebook as Presto and later rebranded as Trino, it enables federated queries where you can join data from multiple data sources (databases, data lakes, object storage) through a single SQL interface without moving the data. Trino's MPP (massively parallel processing) architecture separates compute from storage, making it ideal for modern data lakehouse architectures. Key mental model: Trino doesn't store data — it's a query engine that coordinates distributed execution across worker nodes, pushing down operations to data sources whenever possible and pulling only necessary data into memory for processing.

What This Cheat Sheet Covers

This topic spans 25 focused tables and 156 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Core Architecture ComponentsTable 2: Query Execution ModelTable 3: Connector ArchitectureTable 4: Catalog ConfigurationTable 5: SQL Dialect and Language FeaturesTable 6: Data TypesTable 7: Query Optimization TechniquesTable 8: Join StrategiesTable 9: Performance Tuning PropertiesTable 10: Resource ManagementTable 11: Memory ManagementTable 12: Fault ToleranceTable 13: Security and Access ControlTable 14: Deployment ModesTable 15: DML OperationsTable 16: EXPLAIN and Query AnalysisTable 17: Session PropertiesTable 18: Monitoring and ObservabilityTable 19: Client Libraries and ToolsTable 20: Metadata and Information SchemaTable 21: User-Defined FunctionsTable 22: Advanced SQL FeaturesTable 23: Data Formats and File TypesTable 24: Trino vs AlternativesTable 25: Starburst Enterprise Extensions

Table 1: Core Architecture Components

ComponentExampleDescription
Coordinator
Single node coordinating query execution
• Parses, analyzes, optimizes, and schedules queries
• manages worker nodes and client connections
• single point of failure without external HA setup.
Worker
Multiple nodes executing query tasks
• Process data and execute tasks assigned by coordinator
• fetch data from connectors and perform computation
• horizontally scalable for increased throughput.
Connector
Hive, Iceberg, PostgreSQL connectors
• Plugin that provides interface to specific data source
• translates Trino operations to native source operations
• enables data source abstraction.

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