Today’s data-driven companies have a choice to make – where do we store our data? As the move to the cloud continues to be a driving factor, the choice becomes either the data warehouse (Snowflake et al) or the data lake (AWS S3 et al). There are pros and cons to each approach. While the data warehouse will give you strong data management with analytics, they don’t do well with semi-structured and unstructured data with tightly coupled storage and compute, not to mention expensive vendor lock-in. On the other hand, data lakes allow you to store all kinds of data and are extremely affordable, but they’re only meant for storage and by themselves provide no direct value to an organization.

Enter the Open Data Lakehouse, the next evolution of the data stack that gives you the openness and flexibility of the data lake with the key aspects of the data warehouse like management and transaction support.

In this session, we discuss the data landscape and why many companies are moving to an open data lakehouse. We will share our perspective on how you should think about what fits best based on your use case and workloads, and how some real-world customers are using Presto, a SQL query engine, to bring analytics to the data lakehouse.


Rachel Pedreschi VP Technical Services, Ahana

Rachel is Vice President, Technical Services at Ahana where her main focus is to ensure the experience with Presto and the Ahana platform is delightful from the start. As a self-styled “Big Data Geek-ette,” she is no stranger to the world of high-performance databases. Rachel has decades of experience in database architectures and data engineering, and is an Apache Druid, Cassandra, Vertica, Informix and Redbrick certified DBA on top of her current work with Presto. Rachel has an MBA from San Francisco State University and a B.A. in Mathematics from University of California, Santa Cruz. She is also a mom / chauffeur / short order cook for 2 busy boys and in her free time.. oh wait… she doesn’t have any free time.