Federated queries in data lakes with Redpanda and Trino

Combining data lakes with streaming data can be complex, but this tutorial demonstrates how to use Redpanda as an event storage platform and MinIO, an S3-compatible storage, to simplify the process. The setup involves using Trino to run federated queries on both static data stored in MinIO and live streaming data from Redpanda. The architecture includes MinIO as the storage layer and Trino as the SQL-based query engine. A Hive metastore and MariaDB are used to manage metadata and schema, while Redpanda leverages its Kafka API compatibility to facilitate event streaming. The tutorial provides a step-by-step guide on setting up the environment using Docker Compose, converting CSV files to Parquet format for efficient storage, and executing SQL queries to combine and analyze both static and streaming datasets. This approach is applicable for various real-time analytics use cases, such as clickstream analytics, infrastructure operations analysis, and sales analysis, and offers scalability and ease of deployment for production environments.

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