Apache Iceberg is an open-source table format that provides a number of benefits over alternative data lake file and table formats, including improved query performance, consistency, and accuracy, while also making it easier to manage and evolve data over time. A key component of a data lakehouse stack is the storage layer, which enables organizations to store large volumes and varieties of data types in a flexible and cost-effective manner. Apache Iceberg tables are well-positioned for sustainable development and enterprise adoption, with many contributors from technology companies including Netflix, Apple, Google, AWS, Stripe, Dremio, and others. Data teams can leverage data from the data lake by moving it into the data warehouse using proprietary formats, or relying on data copies to meet Service-Level Agreements (SLAs) for performance. The result is a lot of complexity and management overhead, particularly as requests for access to data in the data lake inevitably increase. A data lakehouse combines the best capabilities of data lakes and data warehouses, enabling organizations to store large volumes and varieties of data types in a flexible and cost-effective manner, while also satisfying a wide range of analytics use cases, including Business Intelligence (BI) and reporting. Fivetran automates the process of bringing data from a variety of sources into cloud data lake storage, providing pre-built connectors for a wide range of data sources, automatic schema detection and mapping, and making it easy to build Iceberg tables. Dremio enables self-service access to Iceberg tables with sub-second query performance, using its semantic layer and query engine based on Apache Arrow, an in-memory columnar format designed for interactive analytics.