Data Lakes have been built with a desire to democratize data - to allow more and more people, tools, and applications to make use of data. A key capability needed to achieve it is hiding the complexity of underlying data structures and physical data storage from users. 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.

Join Jason Hughes, Technical Director at Dremio, for this webinar to learn the architectural details of why the Hive table format falls short and why the Iceberg table format resolves them, as well as the benefits that stem from Iceberg’s approach.

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