Guest To help you make the most of Hadoop, let's look at the promise of big data analytics, and how to avoid expensive, disillusioning failure.

Apache Hadoop, the open source project that arguably sparked the Big Data craze, turned 10 years old this week. The project's founder, Cloudera's Doug Cutting, waxed nostalgic as vendors in the ...

Isotopes, co-founded by Arun Murthy, launched a sophisticated analytics agent. Arun was one of the creators of Hadoop who ...

Hadoop, an open source framework that enables distributed computing, has changed the way we deal with big data. Parallel processing with this set of tools can improve performance several times ...

Big on Data bro Andrew Brust's recent post on the spring cleaning of Hadoop projects evidently touched a nerve, given the readership numbers that went off the charts. By now, the Apache Hadoop ...

It is hard to think of a technology that is more identified with the rise of big data than Hadoop. Since its creation, the framework for distributed processing of massive datasets on commodity ...

Fortunately, there are alternatives to Hadoop when it comes to big data projects. While not applicable to all situations, I've found that a Hadoop alternative can save time, money and slash risk.

If Hadoop is leaving your data lake project all wet, you may be a good candidate for an emerging architectural concept called the big data fabric. As industry experts explain, big data fabrics bring a ...

As enterprises work through big data projects, one trend that I’m seeing is the adoption of cloud-based data warehousing and data lake solutions as alternatives to Hadoop projects.

For many, Big Data is synonymous with technologies and projects such as Hadoop, Hive, Cassandra, Pig and others.