EMC’s Pivotal seeks to expand out into providing platforms that will give enterprise the ability to take advantage of big data analytics in the cloud—by adding the advantage of using VMware cloud, AWS, or OpenStack—and this also represents a move by VMware and EMC to embrace open source and open clouds. Both VMware and EMC only just announced the formation of Pivotal last month amidst much fanfare and speculation and only now we’re getting more details as to how the platform will manifest.

Many people believed that Pivotal would focus on VMware instead of outside cloud providers, but being “cloud agnostic” means that the product could be used anywhere and therefore would see more adoption. Most importantly the world of big data rises out of an open adoption and even open source and being closed off or proprietary to a particular vendor or hardware would tend to injure the enterprise’s ability to adopt them onto their already-existing infrastructure.

Pivotal intends to focus on HTFS (Hadoop’s distributed file system) as their foundational storage technology and this will put them in a place where the product will successfully run on a lot more hardware (or even virtualized hardware.) Once again showing that Pivotal is attempting to avoid lock-in. This also places Pivotal’s product into an interesting space when it comes to developing for and supporting big-data platforms.

By embracing openness and open source systems such as Hadoop, Pivotal also sets themselves up to be easily integrated. As an open source product for Big Data this also means that developers will not need to learn or educate themselves on a whole new system, they’ll be adding Pivotal’s product to their already broadening big data toolset when it’s attached to their already data-centric infrastructure.

You may want to seek to around 2:15s in the video due to a technical issue; above is Jeff Kelley speaking to Pivotal’s current role in the EMC and VMware strategy.

Speaking at Accel Partners Symposium VMware’s VP of Cetas Cloud and Big Data Analytics Dr. Muddo Sudhaker explained that “by integrating the infrastructure natively within Hadoop, Pivotal analytics opens up Big Data analytics to a new class, providing both real-time query responsiveness and eliminating the need to move data back and forth between Hadoop and separate analytic databases.”

Pivotal and the world of CloudOps and DevOps

The concept of being “cloud agnostic” is becoming much more of a selling-point for products that use the cloud as a primary source of data-flow. As it’s been said “data has gravity” or at least it has mass and inertia and so does cloud infrastructure, as enterprise and even small-medium businesses buy into even virtualized or cloud solutions for their data centers they end up focused on a single vendor and have difficulty moving to another one just to promote or define a new Big Data solution.

For the CloudOps team, this also means that grabbing something like Pivotal is as simple as spinning up a new HTFS instance-set and then letting it work with the hardware in the private, public, or hybrid cloud that the team already has running. It also means that the data already stored in that cloud won’t need to move very far to be used.

Reading into Sudhaker’s comments about data movement it also appears that Pivotal is trying to dampen the total inertia that Big Data might have in a business by making sure it doesn’t need to move as far in order to do work. By wedding the analytics database, the Hadoop system, and the data sources, it means that not only does the business need to invest in less real or virtual hardware; but it also means that the CloudOps and DevOps teams won’t need to worry about as many virtual moving parts.

The view from the cloud and dev appears to show that Pivotal (via EMC and VMware working together) intends to to lower the complexity faced by developers and ops teams when working with Big Data and that’s just good business sense all around.