Taking Another Stab At Massively Parallel Data Analytics
For many years, and quite a long time ago in computer time, Hadoop was seen as the best way to store and analyze mountains of unstructured data. …
For many years, and quite a long time ago in computer time, Hadoop was seen as the best way to store and analyze mountains of unstructured data. …
High performance computing workloads simulating all manner of things can produce a veritable mountain of data that has to be sifted through. …
There is something weird about storage companies that were started around the same time as the Great Recession. …
The days of the disk drive have been numbered for so long that it is hard to take any prediction of its demise seriously. …
Enterprises are creating huge amounts of data and it is being generated, stored, accessed, and analyzed everywhere – in core datacenters, in the cloud distributed among various providers, at the edge, in databases from multiple vendors, in disparate formats, and for new workloads like artificial intelligence. …
If memory bandwidth is holding back the performance of some of your applications, and there is something that you can do about it other than to just suffer. …
The IT industry, like every other industry we suppose, is in a constant state of dealing with the next bottleneck. …
DataStax, the driving force behind the ongoing development of and commercialization of the open source NoSQL Apache Cassandra database, had been in business for nine years in 2019 when it made a hard shift to the cloud. …
Nearly two years ago, Hewlett Packard Enterprise rolled out a new battle plan for storage and a new kind of storage array to implement it. …
What good is a floating point operation embodied in a vector or matrix unit if you can’t get data into fast enough to actually use the compute engine to process it in some fashion in a clock cycle? …
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