Keynote: Presto – Swiss Army Knife for the Lakehouse – Tim Meehan
Presto has long been known for its ability to bridge together multiple sources of data using a single consistent language. Learn about the future direction and initiatives that will make Presto even more convenient, reliable and efficient for the Lakehouse.
Ending DAG Distress: Building Self-Orchestrating Pipelines for Presto – Roy Hasson, Upsolver
Ending DAG Distress: Building Self-Orchestrating Pipelines for Presto – Roy Hasson, Upsolver dbt and Airflow is a popular combination for creating and scheduling batch data modeling and transformation jobs that execute in a data warehouse like Snowflake. Presto users querying the data lake need a similar solution that is simple to use and makes it easy to ingest, model, transform and maintain datasets, without having to write or manage complex DAGs. In this session you will learn how Upsolver built a tool that allows engineers, developers and analysts to write data pipelines using SQL. Pipelines are automatically orchestrated, are data-aware and maintain a consistent data contract between each stage of the pipeline. You will also learn how to introduce the idea of data products into your company to enable more self-service for your Presto users.
The Past, Present, and Future of Presto – Philip Bell, Meta
PrestoDB recently underwent major architectural updates as the Presto Foundation grows membership and is looking to vastly grow the number of new commits and forks. Achieving this desired end state required successful refactoring and improving of Presto’s already impressive speed, efficiency, reliability, and extensibility. Establishing PrestoDB as a premier Open Source project required a major commitment of time and resources from Meta to ensure the community can benefit from this project for years to come, as well as positioning PrestoDB to evolve beyond what Meta alone could create. Members of the Presto Foundation need more of you to be involved in this major evolution in Presto’s history and core components, and bring your own inventive ideas to the mix.
Querying streaming data with Presto, Amazon Athena and Upsolver
In this session, Yoni will present on querying streaming data with Presto and Amazon Athena including performance, data partitioning and compaction. In addition, we will demo using the Upsolver platform with Amazon Athena. In addition, he will share what they are working on with Prestodb.
Benchmarking Continuous Data Processing on Snowflake with Upsolver – Sean Spediacci, Upsolver
In this talk, we provide a glimpse at the results of our latest benchmark test which compares the speed and cost of processing data inside Snowflake (ELT) vs. processing and serving prepared live tables from a data lake using Upsolver (ETL).
Presto, Today & Beyond – Dipti Borkar, David Simmen, Girish Baliga & Biswapesh Chattopadhyay
In this PrestoCon talk, team of community experts share Presto evolution, Today & Beyond
The Data Lake House: Powering Open Architecture in the Cloud – Ori Rafael, Upsolver
Ori Rafael, Co-founder and CEO of Upsolver, will present the Cloud Lake House as the foundation of an open data lake architecture built on Apache Parquet. Ori will explain how this architecture supports diverse analytic consumers and use cases, from open-source Presto to proprietary data warehouses.