Using Trino for Your Data Transformations

Trino, a SQL-based query engine originally developed by Facebook in 2012, was designed to address the limitations of Hive in managing large data volumes by offering a fast, distributed solution for both interactive and batch workloads. Over time, Trino has evolved beyond its initial purpose, thanks to enhancements like fault-tolerant execution mode, which improved its robustness by allowing queries to resume from the point of failure rather than restarting entirely, thus enhancing efficiency and reducing resource usage. Trino's ability to connect and perform operations on various data sources using ANSI SQL has made it a popular choice for data transformations, often in conjunction with dbt, a SQL transformation tool that integrates well with Trino to create scalable and efficient data transformation pipelines. The synergy between Trino and dbt allows organizations to leverage SQL's accessibility for data engineers, facilitating the construction of modular data pipelines that can handle complex transformations across diverse data environments.