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Iceberg and Trino highlight enterprise demand for cross-platform data lake functionality

  • Apache Iceberg, the database table format project, is providing full database functionality on top of cloud object stores with open-source tools.
  • Created by two Netflix engineers to overcome issues with the company's Amazon S3-stored media streaming files, Iceberg demonstrates how the separation of storage from compute in modern data stacks has allowed scalable, cost-effective computing and improved interaction between systems.
  • Users can work with any analytics engine by employing Iceberg to enable all compute engines to interact with common data foundations.
  • Meanwhile, open-source Trino distributed query engine, developed to replace Facebook's 300-petabyte Hive data warehouse, responds to the need for fast, ad-hoc analytics queries over big data file systems.
  • Starburst, the commercial developer of Trino, is taking steps to make it simpler to build apps on data lake architectures by offering a fully managed Icehouse data lake to support near-real-time data ingestion into a managed Iceberg table at a petabyte scale.
  • Iceberg's modern table format continues to attract enterprise interest, with Google, Snowflake and Databricks among the companies that have announced support for it according to its creator Ryan Blue.
  • In its earnings call at the end of February, Snowflake noted that customer adoption of Iceberg tables could create “revenue headwinds” for the firm.
  • Iceberg provides a strong technical foundation and an open community, where it's owned and controlled by the Apache Software Foundation. Blue wants the project to be a foundational layer in data architecture for solving all of the problems.
  • Assembling the best analytical engines in cost-effective solutions is important because people want to move to more cost-effective solutions when there's too much data to process, according to Dain Sundstrom, chief technology officer of Starburst.
  • Iceberg combines Trino and Iceberg storage, and offers the best data lake format in Sundstrom's opinion.

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