Update from TSC | Demo from compute.ai (July 26, 2023)
Update from Presto Technical Steering Committee Chair Tim Meehan Hear the latest from Tim Meehan, Chair of the Presto TSC. Also learn how compute.ai enables high performance SQL with Presto
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.
HermesDB – Integrated Presto with a lucene-based Query Engine – Yue Long, Tencent
HermesDB is the next generation of OLAP engine at Tencent with the architecture featuring separation of storage and calculation. HermesDB characterizes efficient indexing files in storage data, equipping with customized Presto as the core query engine. With the help of Presto connector, HermesDB could not only support full ANSI syntax but also ultilize Apache Lucene as underlying computer core. Besides, we are in the progress of improving the end-to-end performance with the newly released Java Vector APIs, acclecerating different kinds of complex computations with SIMD instructions. According to the benchmark(SSB) we have, HermesDB outperformances other mainstream C++ based MPP engines.