Bodo is a SQL and Python data processing platform powered by advanced compilers and MPI parallelization technologies. Bodo fits into your existing data stack so you can quickly get up and running—while keeping what works in place.
The Bodo compiler and MPI parallelization technologies were developed through years of R&D. Bodo is architecturally up to 20x more efficient than existing data warehousing and Spark data processing engines.Take a peek under the hood
Are large data transformations and joins resulting in long-running and expensive SQL/Python jobs? Bodo's parallel architecture provides the most efficient design for query execution, resulting in far shorter query run times and greatly reduced cloud spending.See our benchmarks
Bodo's fast data transformations will help you meet or exceed even the most stringent SLAs across a variety of data use cases. Deliver the freshest data to your analytics teams for better, faster data-driven decision-making.Learn more
Data engineers can focus on developing, validating, and testing their data transformation workloads—instead of being bogged down by manual query or infrastructure performance tuning. Speed up development cycles, streamline developer workflows, and enable collaboration through shared workspaces.Learn more
This is the real deal. Bodo built on the success of Numba to combine compiled Pandas and automatic parallelism (with MPI) to get incredibly fast data processing using simple syntax. It is particularly great for ETL. It can make your code using Python *fast*—simply.
With a high-performance computing (HPC) framework like Bodo, the execution of numerical operations can be made significantly more efficient without having to provision clusters or extensively rewrite code manually.
With Bodo, we are now able to scale up our MBA (market basket analysis) metrics to longer periods with much better results. On the same infrastructure, Bodo takes around 6 mins for the workload that takes Databricks 1.1 hours.