omega|ml is an innovative Python-native DataOps and MLOps platform that provides a ready-to-use data science workbench, development and runtime environment.
It is unique in its “single line of code” approach and open architecture, providing a fully integrated cloud-native and scalable compute and storage facility for all your analytics needs. Built on well-known open-source technology, omega|ml removes vendor lock-in and saves up to 90% of the time investment compared with custom-engineered solutions.
At the core, omega|ml is provided as open source. Its open architecture uses a unique plug-in system that enables DataOps teams to keep their existing data science libraries such as Pandas, Tensorflow, Keras and PyTorch, while gaining the ability to easily store, process, train and run all data and models.
omega|ml’s integrated hybrid analytics storage, built on MongoDB, provides the Python-native and Pandas-like API familiar to most data scientists. This allows any-size datasets to be processed at ease and without the excessively high memory needs or computation delays of other solutions.