Accelerating Hadoop's Big Data Momentum
Some may consider the Pivotal and Hortonworks partnership on Apache Ambari simplistic or even mundane. However, without better-quality operations tools, Hadoop seems unlikely to evolve enough, or quickly enough, to fully achieve what its proponents envision. The fact is that in many or even most cases, sublime achievement requires a mundane foundation.
08/05/14 6:20 AM PT
The concept of "collaboration" has become such a messaging mainstay that it often verges on cliché. So, does the recently announced Pivotal and Hortonworks plan to improve Hadoop operations by collaborating on Apache Ambari qualify as anything new or special?
In fact, it does.
Innovation vs. Reliability
Hadoop is a core technology in many or most modern Big Data analytics solutions and strategies, but it has struggled to develop the practical features enterprises demand for dependable management and performance.
Despite Hadoop's numerous attractions -- and there are many -- denying or delaying those features likely would hobble wider adoption.
This challenge is anything but unique to Hadoop. In fact, Linux and some related efforts suffered similarly painful paths to maturity. Open source collaboration can encourage -- and has delivered -- marvelous innovations, but it often stumbles in areas that benefit from more linear development efforts.
More Efficient and Effective
In his commentary on the Pivotal deal, Shaun Connolly, Hortonworks' VP of corporate strategy, specified how Apache projects can span "five distinct pillars to form a complete enterprise data platform: data access, data management, security, operations and governance."
Per the two companies' statements, this new effort aims to leverage their considerable skills and open source experience to improve Hadoop operations and make Apache Ambari the standard management tool for Hadoop.
So what exactly is Apache Ambari? A framework for Hadoop provisioning, managing and monitoring that allows administrators to
- easily provision Hadoop clusters of virtually any size;
- simplify Hadoop cluster management tasks, including controlling service and component lifecycles, modifying configurations and managing growth;
- efficiently monitor Hadoop clusters by preconfiguring alerts and visualizing operational data; and
- effectively integrate Hadoop (via a RESTful API) with existing data center tools, like Microsoft System Center and Teradata Viewpoint, and operational processes.
A Big Big-Data Future
The main "wood behind the arrowhead" in this collaboration are the Pivotal engineers who will combine parts of the company's installation and configuration manager technologies in Ambari to substantially expand its core capabilities.
Some may consider this partnership and its goals simplistic or even mundane. However, without better-quality operations tools, Hadoop seems unlikely to evolve enough, or quickly enough, to fully achieve what its proponents envision.
The fact is that in many or even most cases, sublime achievement requires a mundane foundation.
Without the foundational operations capabilities enterprises demand -- and that the Pivotal and Hortonworks collaboration will deliver -- Hadoop's Big Data future could have been far smaller than many hope or believe it will be.