Apache Iceberg™ on Quanton: 3x Faster Apache Spark™ workloads

Onehouse has introduced the Quanton engine, which significantly enhances Apache Iceberg workloads on Apache Spark by offering up to three times better performance on industry-standard benchmarks without altering existing Spark jobs or SQL. Quanton's unique approach combines faster runtime and smarter data processing, outperforming industry leaders like Databricks Photon in terms of price-performance without additional cluster costs. Designed to maintain compatibility with existing workflows and open table formats, Quanton optimizes execution runtime and storage engine layers to address inefficiencies in traditional Spark environments. It accelerates data operations through techniques such as SIMD vectorized execution and storage-aware optimizations, offering substantial improvements in ETL tasks, including join, filter, and update operations. The engine achieves better performance for mixed workloads by integrating seamlessly with Iceberg's metadata and employing advanced techniques like asynchronous indexing and compaction. Onehouse provides tools like the Cost Analyzer for Apache Spark to help users assess potential savings and performance gains with Quanton, which is fully compatible with existing Spark infrastructures.