IBM extended Big SQL, which was formerly exclusive to the IBM Open Platform (IOP), to the Hortonworks Data Platform (HDP) in September 2016. I recently spoke with Berni Schiefer, an IBM fellow in the IBM Analytics group, to learn more about the offering and the ongoing IBM focus on SQL.
Although formerly exclusive to the IBM Hadoop Platform, the extension of Big SQL to the Hortonworks Data Platform (HDP) meets the challenge of complex data warehousing queries on Hadoop. See what Paul Yip, worldwide product strategy for Hadoop and Spark at IBM, has to say about what this transition
Performing programmatic actions on data across services is quite possible in today’s technology ecosystem. And now, the transfer of data across services such as the dashDB data warehouse and deploying it in new environments is also possible. However, the questions often asked by customers center on
Openness was a common refrain at Insight 2015, and the opportunities of open systems, technologies and the IBM analytics platform are abundant. Check out some observations from the conference and a few shining examples from its demo center.
IBM® InfoSphere BigInsights upcoming release includes Big SQL 3.0, bringing performance, security and improved ROI to Hadoop projects. This is an important leap forward to seamlessly transitioning analytic applications from relational database management systems (RDBMS) to Hadoop distributions. In
Despite the rise in popularity of big data technologies like Hadoop, organizations today face a serious big data skills shortage. In this video, Christy Maver of IBM Big Data marketing discusses how the IBM Big Data Quick Start Program provides free, non-production downloads of key big data
If your new year resolutions include getting more familiar with big data and honing your skills, here’s a quick, easy-to-scan glimpse of some highlights you might have missed during your holiday celebrating. Think of these resources as items on the grab-and-go aisle in the café. Add a latte and get
It’s hard to have a conversation about big data without talking about Hadoop. Sure, it can be done. You can discuss how big data is all data, how big data without analytics is just “same ol’ data”, or how the implications of governing big data are even more severe than in a traditional environment
Big data technologies like Hadoop are providing enterprises a cost-effective way to store and analyze data. Enterprises are looking at using Hadoop to augment their traditional data warehouse. Compared to traditional data warehouse solutions, Hadoop can scale using commodity hardware and can be
Many people want SQL, the query language of the past two decades, to work on Hadoop. Derrick Harris of GigaOM outlined the approaches of 13 different vendors with their cleverly named projects in his Feb 2013 article. Recently, Information Week’s special coverage series on big data included an
Hadoop is fundamental to the future of big data. Users are adopting Hadoop for strategic roles in their current data warehousing architectures, such as extract/transform/load (ETL), data staging and preprocessing of unstructured content. Hadoop is also a key technology in next-generation massively
One of the recurring themes at yesterday’s “Big Data at the Speed of Business” launch was comsumability, which is just a fancy word for ease of use. Let’s face it, Hadoop can be hard; big data can be complicated, and there’s certainly a learning curve involved in being able to leverage most big