Hadoop Summit kicks off today. And while I could start this post by providing a long diatribe about the momentum and disruption happening in the big data space, I feel I can spare you that point. This momentum is being felt across every sector and is addressing almost every new data workload coming into existence. The argument no longer needs to be made.
The world of data platforms is forging forward with increasing velocity. To stay relevant in today’s Big Data conversation, technologies must implement features and enhancements at a swifter cadence than legacy technology. The only way this is possible is by orchestrating the worldwide execution of an open ecosystem of participants. Consider Apache Hadoop; this level of advancement would not be possible without a broad network of developers and engineers working together to rapidly innovate to solve new problems. In addition to just fixing the issues users have with Hadoop, the community is changing the perception of how users can leverage it. Once a go-to tool for large batch processing jobs, Hadoop is changing to address the needs of multiple workloads simultaneously such as streaming and interactive workloads all done at the same level of scale of the original batch jobs.
At this year’s O’Reilly Strata event we will showcase our support of the newest genesis of the Hortonworks Data Platform (2.0), a release that we believe represents a paradigm shift in the perception of what you can use Hadoop to accomplish.
A few weeks ago we told you about our two Data Services for Hadoop-based applications, the Managed Big Data Platform service (in Unlimited Availability) and the Cloud Big Data Platform (in Early Access). Working hand in hand with Hortonworks, we are giving you a choice of architectures for your Hadoop applications, whether you need a custom-built Hadoop architecture based on specific dedicated hardware, or a dynamic, API-driven programmable Hadoop cluster in our public cloud.
Not all data is created equal. Each company’s data strategy needs to be laid out with consideration and thought as to what the future demands of the system might be. Although HadoopTM has its roots firmly planted in the JBOD and bare metal camps, users are increasingly trying to find ways to split up data processing based on workload requirements and on the nature of the type of query they are running.
The demand for Big Data solutions continues to grow, and to help you tackle Big Data workloads, we have partnered with Hortonworks, the premiere open-sourced Apache HadoopTM enterprise distribution, to provide application support and best-in-breed architecture design.
We want to take the headache out of deploying and using Big Data solutions. And today, through a strategic partnership with Hortonworks, a leader in Apache Hadoop development, implementation, support, operations and training, we will do just that.