Enterprise-Scale Data Engineering with Python: Evaluation of Bodo Derived from the TPCx-BB Q26 Benchmark

Bodo is a platform that simplifies data engineering workloads for large-scale data processing, offering 10x faster performance and 90% AWS infrastructure savings compared to Apache Spark. It uses native Python APIs, eliminating the need for complex setup and parameter tuning, making it easier for data scientists and engineers to use and maintain. Bodo scales linearly with data size and node count, while Spark struggles with large datasets and requires additional tuning. The platform achieves significant performance improvements even without using AWS Elastic Fabric Network (EFA). By providing a more efficient and cost-effective alternative to Spark, Bodo aims to advance the data analytics area by offering 10x or more simplicity and performance improvements.