Qbeast

Qbeast is an optimization engine that works cooperatively with any Lakehouse platform (Databricks, Starburst, Snowflake, Dremio, and others) to deliver fast, flexible, and cost-efficient queries through smarter data layout by using patented multidimensional indexing.

Unlike solutions that force a trade-off between cost and speed, Qbeast reduces compute and data-movement overhead—so you get both lower costs and better performance. The result is a more efficient and adaptive Lakehouse that responds seamlessly to changing workloads.

As data volumes grow, open table formats struggle with speed and rising compute costs across different query engines. Qbeast’s approach uses multidimensional indexing and optimized data layout to reduce compute needs and accelerate performance on Spark, Trino, Presto, and beyond. The company’s platform accelerates analytics 2.5×, cuts AI training time by 62%, and reduces data processing requirements by 70%.

Headquartered in Bellevue, Washington, Qbeast also has offices in Barcelona and Bengaluru. It was founded by Srikanth Satya, Cesare Cugnasco, and Flavio Junqueira. 

A cloud infrastructure veteran who was formerly with AWS and Microsoft Azure, Srikanth is also an accomplished cricketer. Cesare Cugnasco holds a PhD in Computer Architecture and an Executive MBA. He specializes in scalable data systems, patented analytics technology, and collaborations with leading tech and industrial firms. Flavio Junq is a computer scientist in distributed systems, with a Ph.D. from UC San Diego and 6,000+ citations for his research. He has held senior roles at major tech companies and co-founded Apache ZooKeeper, BookKeeper, and Pravega.