Keynote Panel: Presto at Scale – Shradha Ambekar, Gurmeet Singh, Neerad Somanchi & Rupa Gangatirkar

Keynote Panel: Presto at Scale – Shradha Ambekar, Gurmeet Singh, Neerad Somanchi & Rupa Gangatirkar

Over the last decade Presto has become one of the most widely adopted open source SQL query engines. In use at companies large and small, Presto’s performance, reliability, and efficiency at scale have become critical to many companies’ data infrastructures. In this panel we’ll hear from three of the largest companies running Presto at scale – Meta, Uber, and Intuit. They’ll share more about their learnings, some of their impressive performance metrics with Presto, and what they envision going forward for Presto at their respective companies.

How Blinkit is Building an Open Data Lakehouse with Presto on AWS – Satyam Krishna & Akshay Agarwal

How Blinkit is Building an Open Data Lakehouse with Presto on AWS – Satyam Krishna & Akshay Agarwal

Blinkit, India’s leading instant delivery service, uses Presto on AWS to help them deliver on their promise of “everything delivered in 10 minutes”. In this session, Satyam and Akshay will discuss why they moved to Presto on S3 from their cloud data warehouse for more flexibility and better price performance. They’ll also share more on their open data lakehouse architecture which includes Presto as their SQL engine for ad hoc reporting, Ahana as SaaS for Presto, Apache Hudi and Iceberg to help manage transactions, and AWS S3 as their data lake.

Presto On Spark: Scaling not Failing with Spark – Ariel Weisberg, Meta & Shradha Ambekar, Intuit

Presto On Spark: Scaling not Failing with Spark – Ariel Weisberg, Meta & Shradha Ambekar, Intuit

Presto on Spark is an integration between Presto and Spark that leverages Presto’s compiler/evaluation as a library and Spark’s large scale processing capabilities. It enables a unified SQL experience between interactive and batch use cases. A unified option for batch data processing and ad hoc is very important for creating the experience of queries that scale instead of fail without requiring rewrites between different SQL dialects. In this session, we’ll talk about Presto On Spark architecture, why it matters and its implementation/usage at Intuit.