The petabyte architecture you cannot afford to miss!
The volumes of data used for Machine Learning projects are relentlessly growing. Data scientists and data engineers have turned to Data Lakes to store vast volumes of data and find meaningful insights. Data Lake architectures have evolved over the years to massively scale to hundreds of terabytes with acceptable read/write speeds. But most Data Lakes, whether open-source or proprietary, have hit the petabyte-scale performance/cost wall.
Scaling to petabytes with fast query speeds requires a new architecture. Fortunately, the new open-source petabyte architecture is here. The critical ingredient comes in the form of new table formats offered by open source solutions like Apache Hudi™, Delta Lake™, and Apache Iceberg™. These components enable Data Lakes to scale to the petabytes with brilliant speeds.
Image: by Hubert Neufeld: https://unsplash.com/photos/7S21XSxKxVk
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