If there’s one thing that characterizes the Information Age that we find ourselves in today, it is streams of data. However, ...

Hadoop achieves this by breaking down large datasets into smaller blocks, distributing them across a cluster of commodity hardware, and processing the data in parallel, which significantly ...

Fast, flexible, and developer-friendly, Apache Spark is the leading platform for large-scale SQL, batch processing, stream processing, and machine learning.

This is a comprehensive Apache Hadoop and Spark comparison, covering their differences, features, benefits, and use cases.

Developing a strategy for the post-Hadoop era – and freeing up time and resources to focus on emerging data challenges.

There are reasons Hadoop has maintained a grip inside some of the largest companies, even still. But that’s officially over, says Vinay Mathur, who heads up strategy at Next Pathway, a company devoted ...

Hadoop might be dead, but that’s not stopping public cloud providers from using it. The latest to make a move is Microsoft Azure, which in July announced that it would begin developing its own ...

Regardless of its long-term prospects, Hadoop remains a pivotal technology in the history of databases. Hadoop was one of the key technologies that broke the stranglehold of relational databases, and ...

Hadoop helped popularize and simplify this analytical use of data in 2010, and since then the technology and techniques involved have developed at a break-neck speed. Hadoop’s project was massively ...