Implementing Lakehouse Architecture with Presto at Bolt – Kostiantyn Tsykulenko, Bolt.eu

Implementing Lakehouse Architecture with Presto at Bolt – Kostiantyn Tsykulenko, Bolt.eu

Bolt.eu is the first European mobility super-app. We have over 100M users across Europe and Africa and have to deal with data at a large scale on a daily basis (over 100k queries daily). Previously we were using a traditional data warehouse solution based on Redshift but we’ve faced scalability issues that were hard to overcome and after doing our research we chose Presto as the solution. In just a single year we’ve managed to migrate to the Lakehouse architecture using AWS, Presto, Spark and Delta lake. We would like to talk about our journey, some of the challenges we’ve encountered and how we solved them.

Delta Lake Connector for Presto – Denny Lee, Databricks

Delta Lake Connector for Presto – Denny Lee, Databricks

Delta lake is an open-source project that enables building a lakehouse architecture on top of existing storage systems such as S3, ADLS, GCS, and HDFS. We – the Presto and Delta Lake communities – have come together to make it easier for Presto to leverage the reliability of data lakes by integrating with Delta Lake. In this session, we would like to share the design decisions and internals of the Presto/Delta connector.

Drag and Drop Query Builder for PrestoDB – Ravishankar Nair, PassionBytes

Drag and Drop Query Builder for PrestoDB – Ravishankar Nair, PassionBytes

You use multiple tools for databases, for example Azure Data Studio for SQLServer access, Toad or SQLDeveloper for Oracle access, MySQLWorkbench for MySQL databases. Imagine we have one tool and we can query any database, bring any table from any catalog to a single canvas! Now you join, the underlying PrestoDB compatible query is generated. Click a button, you get the profiled data, including distributions and correlations. An amazing tool in action.