Growing data volume, variety, and velocity has made it crucial for businesses to implement architectures that efficiently manage and analyze data, while maintaining data integrity and consistency. In this post, we show you a solution that combines Apache Iceberg, Data Build Tool (dbt), and Amazon EMR to create a scalable, ACID-compliant transactional data lake. You can use this data lake to process transactions and analyze data simultaneously while maintaining data accuracy and real-time insights for better decision-making.
Challenges, business imperatives, and technical advantages
Traditional data lakes have long struggled with fundamental limitations. For example, the lack of ACID compliance, data inconsistencies from concurrent writes, complex schema evolution, and the absence of time travel, rollback, and versioning capabilities. These shortcomings directly conflict with growing business demands for concurrent read/write support, robust data versioning and…
