Bodo's mission is to create high-performance technology that enables organizations to keep up with the scale, speed, and use cases that today’s data environment demands.
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Bodo started at Intel Labs as part of a project to democratize machine learning and enable parallel learning for everyone.
Bodo is a next-generation SQL and Python data processing platform powered by advanced compilers and MPI parallelization technologies. Bodo radically enhances data engineering by providing 10x or greater improvements in speed, scale, and cost efficiency.
Built from years of research by compiler and High-Performance Computing (HPC) experts, Bodo brings HPC levels of performance and efficiency to data engineers without any new language API layers or performance tuning.
Founded in 2019, Bodo has endorsements and investments from Dell Technologies Capital, Snowflake, KDT Ventures, AMD, In-Q-Tel, and various VC firms, as well as major enterprise customers.
Bodo can be translated into "run" or "accelerate", and our technology does just that.
Bodo is the first extreme-performance SQL and Python data processing platform. It is the culmination of years of research in academia and industry by the creators of the first auto-parallelization compiler technology. This technology has long been a “holy grail” for researchers working on solving the gap between simplicity and performance in computing. By democratizing access to parallel computing, we aim to accelerate data insights, ML, and AI in ways the industry can’t yet imagine.
Most authorities agree that Moore’s law is being challenged. Data sets continue to grow, driven principally by AI and ML. In order to keep pace with compute demands, we at Bodo believe that taking advantage of parallelization, combined with today’s abundant cloud CPU resources, is the best answer. With the advent of mega-cloud vendors bringing cost-effective access to this processing power, combining HPC-style parallelization to this infrastructure will again accelerate computing performance and access to computing speed.
Today’s data scientists and developers face daunting learning curves, glue code, and special-purpose hardware/software combinations. Achieving extreme performance has therefore meant giving up programming simplicity and velocity. Bodo, instead, believes that extreme performance can be achieved and made accessible to everyday developers through the use of inferential, auto-parallelization compilation, which is far more accessible to the developer.
Open source communities, and the software industry overall, have generated a plethora of add-in libraries and frameworks to enable scale-out programming for developers and data scientists. However, none of these solutions have brought true linear scaling, and all require some new APIs and/or steep learning curves. They have all failed to consider a deeper look at parallel programming fundamentals and have overlooked considering JIT compilation as a solution. The inefficiencies of the underlying approach drive the complexity of the systems and features that most solutions offer today. In contrast, Bodo adheres to the most advanced parallel computing principles while making it accessible for programmers so they can focus on solving the problems that matter.
Bodo has offices in Pittsburgh, PA and San Mateo, CA—but we are mostly remote. The people we need don’t live in a single area code, so we hire the right people wherever they happen to live.
