We know that data management today is changing completely. For decades, businesses relied on data warehouses, which stored information in an appropriate manner. They are structured, governed, and quick to extract information from, although expensive and rigid in nature. In contrast, data lakes are more efficient and allow for the storage of enormous amounts of data regardless of structure. However, the emergence of the data lakehouse architecture combines the benefits of the data lakes and data warehouses. Lakehouse models allow the retention of the flexibility provided by data lakes while integrating the reliability, governance, and performance of a data warehouse.

The most notable open-source table format created for large-scale data analytics is Apache Iceberg. Iceberg is at the forefront of this transformation and enhances the value of data in the lakehouse architecture. Additionally, Iceberg provides solutions for many of the problems that data lakes face, including schema evolution, ACID transactions, data consistency, and query performance.