Vendors » EMC
Hadoop has matured at a rapid rate since it broke into the mainstream several years ago. With billions in venture funding, an eager community of developers, and a thriving ISV community, the open source big data platform seems poised to take a big step into the wider enterprise. But according to Cloudera’s chief strategy officer Mike Olson, Hadoop’s next big move may be to just disappear. Olson predicted Hadoop’s disappearance during a keynote address at last week’s Strata + Hadoop Read more…
You may use Hadoop to suck up all kinds of data, and you may even analyze some of it there. But any insights you glean should not exist in a vacuum. To succeed in this big data world, you must put your insights into use—that is, you must operationalize them–and that sometimes requires a different set of skills and technologies outside of traditional Hadoop. Hadoop may be the poster child for big data, but it’s not the whole story. While Read more…
Forget the data science–in some organizations, just getting access to a Hadoop cluster is a major obstacle. With today’s launch of EPIC, the software virtualization company BlueData says analysts and data scientists can self-provision a virtual Hadoop cluster in a matter of seconds, enabling them to iterate in a faster and more agile fashion. If things go as planned, BlueData‘s new EPIC product will usher in a new level of failure for Hadoop users around the world. “If you want Read more…
There is a lot of debate in the big data space about tools and technology, and which ones are best. Is SQL better than NoSQL? Hadoop or Spark? What about R or Python? Of course no single tool or technology is the best for all situations, and you would do well to pick the right tool or technology for the job at hand.
While still in its infancy, the big data technology trend has made a lot of substantial progress since it gained traction at the beginning of this decade. The year 2013 was a big year with advances being made in virtually every quarter of the space. In this feature, we take a look at some of the significant trends that have crossed our desks in the past year — wrapped up and presented to you with a pretty bow. Out with the old, in with the new — it’s the Datanami 2013 Year in Review!
News In Brief
Not long ago, the rules for what constituted a data warehouse were fairly well defined. The schema was fixed, you could say, and was based primarily on relational database technology designed to process structured data. My, how times have changed. Last week, Gartner for the first time accepted non-relational technologies–including those based on Hadoop and NoSQL–in its annual Magic Quadrant for Data Warehouses report.
Among Hadoop distributors, MapR Technologies’ product offering is the strongest, Amazon Web Services has the biggest Hadoop market presence, and IBM and Pivotal Software have the best market strategy, according to a new Forrester Wave report released yesterday that slices and dices the Hadoop market and analyzes the various Hadoop product offerings and business strategies.
With Oracle’s OpenWorld going on this week, there is a lot of talk about what the future holds for IT. Two of the most powerful CEO’s in IT took the stage this week to discuss the trends that are shaping the future.
Today, April 15, 2013, is tax day in the United States. Millions of Americans are assuredly scrambling to file their returns today and most will be doing so electronically. Specifically, the IRS expects 80 percent of tax returns, or 250 million, to be filed online. That represents a significant big data problem in identifying the veracity of said filings.
Greenplum and EMC announced a 1000-node test cluster that will be used by select institutions to validate code running on the Hadoop framework. The companies say the the new service will further big data development by providing an environment to….
This Just In
RainStor, provider of the most efficient enterprise database for Big Data, has successfully completed product testing, resulting in validation of its database on EMC Corporation’s Isilon Scale-Out network-attached storage (NAS) running on the Hadoop Distributed File System (HDFS).