Big Data refers to massive volumes of structured and unstructured data that are too large or complex for traditional data processing tools. It's not just about size — it's also about the insights that ...

Getting timely, smart insights out of the massive amounts of data that organizations are sitting on starts with a mindset ...

Modern computing has many foundational building blocks, including central processing units (CPUs), graphics processing units (GPUs) and data processing units (DPUs). However, what almost all modern ...

Parallel processing is an idea that will be familiar to most readers. Few of you will not be reading this on a device with only one processor core, and quite a few of you will have experimented wit… ...

AWS recently announced a distributed map for Step Functions, a solution for large-scale parallel data processing. Optimized for S3, the new feature of the AWS orchestration service targets interactive ...

Snowflake’s cross-cloud platform provides quick, reliable, and secure access to all your data. Snowflake for Data Lake Analytics combines unstructured, semi-structured, and structured data of any ...

Dask: Parallelizes Python data science libraries such as NumPy, Pandas, and Scikit-learn. Dispy: Executes computations in parallel across multiple processors or machines.

As the company name suggests, Swarm64 leverages parallel processing to accelerate and scale PostgreSQL performance, spinning up 64 parallel threads to execute queries. The 4.0 version released last ...