Startup Galactic Exchange Spins Up Hadoop, Spark Clusters in Minutes

Is it possible to spin up a free Hadoop or Spark cluster in only five minutes? That is what startup company Galactic Exchange is billing as its calling card.

The company is fresh out of stealth mode and wants to cater to those who may not have any Big Data experience at all. Here are more details.

Galactic Exchange has a beta product, ClusterGX, coming out this week. It is built to work on Linux, Windows or Mac OS, and can reportedly be installed nearly instantly by those with no experience in building clusters, Hadoop or Spark.

ClusterGX is built around Apache Mesos and Docker Inc.’s container technology. Analysts are weighing in. According to Mike Matchett of Taneja Group:

"Ease of use aside, Galactic Exchange is pioneering advances in two distinct areas. They are not encumbered by legacy VM constraints, so they are catching the Container wave and creating this new ground-breaking management approach by both using and enhancing the flexibility and agility of a Docker-centric architecture. Second, by moving the complexity of cluster and Hadoop/Spark management into their cloud service while preserving all big data and computing nodes on-premise, they are really simplifying and accelerating customer adoption. They are essentially unlocking the opportunity for many more businesses to take easy advantage of new analysis solutions, data lakes, and even IoT opportunities. We view this smart cloud-centered management approach as a very positive trend which we are starting to also see in a number of other areas."

And Nik Rouda at ESG-Global said:

"The Big Data market has grown rapidly to be a multi-billion dollar industry but it is generally recognized that continued complexity is the greatest barrier to broad adoption. Anything which helps reduce this complexity and accelerate the time to value for an organization must be a considered a very positive thing."

 Galactic Exchange reportedly wants to expand beyond Hadoop and Spark clusters to work with other popular Big Data technologies as well.

You can find out more here.