The Bodo platform powers fast, efficient big data processing for Python data teams. Bodo’s Inferential Compiler delivers high-performance style computing for data-intensive processing. Bodo analyzes the syntax of regular Python code to determine opportunities for parallelization and infers an optimal code structure to generate parallelized binary code. The Bodo platform also includes: High-performance connectors, parallel I/O, SaaS notebooks facilities, and resource management within the cloud infrastructure.
The clearest speed and efficiency improvements come with using Bodo with other supported Python libraries, as well as with large data processing intensive use cases that benefit from parallelized execution.
Bodo’s linear scaling capability is most noticeable with efforts involving jobs of 100’s of GBs, hundreds of millions of Dataframe rows, and compute times approaching/exceeding 1h. Bodo best addresses the following use cases and pain points.
Long Processing Time
Time to Translate to Better Performing Languages
Lack of Parallel Programming Skills
Lost Time by Analytics Team Awaiting Data
Data Prep and ETL
Ml Model Training
Bodo compiles functions into efficient native parallel binaries, which require that the operations used in the code are optimized by Bodo. This excludes some Python features. Optimized libraries include:
Basic CPUs (e.g., on-premises, AWS, Google Cloud, Azure). Bodo does not require any special-purpose hardware or networking.