Trino Data Source Integration: General Availability — ADOC 26.3.0

Trino, a distributed SQL query engine designed to federate queries across various data sources, faces challenges in data observability due to its architectural design, which makes it efficient yet difficult to monitor data reliability, freshness, consistency, and quality. Traditional observability tools fail to address schema changes, data quality issues, and freshness validation effectively in Trino environments, leading to gaps in data assumptions versus reality. The Acceldata Data Observability Cloud (ADOC) aims to bridge these gaps by providing a fully integrated data source for Trino with capabilities such as automated metadata crawling, profiling, anomaly detection, schema drift monitoring, reconciliation, and freshness tracking within the same observability framework used for other data stack components. ADOC's approach contrasts with traditional log-based methods by actively crawling and profiling data assets, offering direct insights into data quality, schema changes, and freshness across various connector configurations. This integration supports two execution engines, Spark and Pushdown, to accommodate different operational needs, though there are limitations to consider, such as the lack of support for certain configurations and the requirement for SSL-enabled connections.

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