Data Lakes have been built with a desire to democratize data - to allow more and more people, tools, and applications to make use of more and more data. A key capability needed to enable more users is the ability to hide the complexity of underlying data structures and physical data storage. The de-facto standard has been the Hive table format, released by Facebook in 2009 that addresses some of these problems, but falls short at data, user, and application scale. So what is the answer? Apache Iceberg. Apache Iceberg table format is now in use and contributed to by many leading tech companies like Netflix, Apple, Airbnb, LinkedIn, Dremio, Expedia, and AWS.

In this talk you will learn:
* The issues that arise when using the Hive table format at scale, and why we need a new table format
* How a straightforward, elegant change in table format structure has enormous positive effects
* The underlying architecture of an Apache Iceberg table, how a query against an Iceberg table works, and how the table’s underlying structure changes as CRUD operations are done on it
* The resulting benefits of this architectural design