Combining AWS services with Apache Iceberg tables lets companies build powerful, cost-effective data lakes

Combining AWS services with Apache Iceberg tables enables companies to create robust and cost-effective data lakes that enhance big data analytics capabilities. AWS offers a comprehensive suite for building enterprise-grade data architectures by leveraging open-source table formats like Hive, Iceberg, Delta Lake, and Hudi, which provide advanced features such as ACID transactions, schema evolution, and time travel queries. These formats, in conjunction with open compute engines like Hive, Trino, and Spark, facilitate high-performance analytics. AWS services such as Amazon Athena, Amazon EMR Trino, and AWS Glue support these frameworks by providing scalable, secure, and efficient data management and processing capabilities. Starburst Galaxy, based on the Trino query engine, further enhances this ecosystem by offering a unified analytics platform that democratizes data access while ensuring compliance and governance. Through a product-based approach, Starburst enables companies to build curated data products, thus improving data access and accelerating decision-making processes across AWS infrastructure.