Forrester recently published the “The Forrester Wave™: Big Data Hadoop Solutions, Q1 2014”, which evaluates solutions from a number of vendors including IBM. Free download of the report is available here It’s nice to see that IBM is recognized as the leader in strategy. The rankings of current offering however require a closer look. At…
Trash Talks? Cloudera? Well, in case you missed it, that’s what was reported in Information Week yesterday. Certainly Hortonworks and MapR had some issues with what Cloudera said, and added their comments to the online article. From my perspective, well, first of all – Kudos to Cloudera for simplifying their packaging – no longer do…
Teradata is legend when it comes to Data Warehouse. Well respected, and I have some good friends who work there. Heck, even I almost ended up working there at one point. But when the Big Data craze and Hadoop came along, Teradata found themselves in a bit of a different position. The last few years…
My opinion of Oracle’s view on Hadoop is that Oracle positions Hadoop primarily a place to “acquire and organize” unstructured data for loading into Oracle Database or Exadata for analysis. To accomplish this, they have a software bundle called “Oracle Big Data connectors” which is an optional add on to the Oracle Big Data Appliance.…
Next up in the video blog series with myself and Dirk deRoos – we discuss Hortonworks. We both have lots of respect for Hortonworks, but we also think there are some differences and capabilities that are worth pointing out relative to the IBM BigInsights offering. Click on the image below to watch this short video.
Following up on last weeks post about Cloudera’s Impala “benchmarketing”, here is the latest video in the Hadoop competitive series – this time Dirk deRoos and I discuss Cloudera and how we think it stacks up relative to IBM’s BigInsights. Click on the image below to watch! (the link now works 🙂
Cloudera recently issued a press release claiming that Impala, their Hadoop SQL engine, is faster than Apache Hive, faster than an unnamed “proprietary database”, scales linearly, has been widely adopted, is production ready, and has an ever increasing list of enterprise features. Sounds impressive – but these bold claims warrant a closer look. Benchmark Games…
Capacity seems to be a common metric for comparison. The trouble is that it is not often an apples to apples comparison. Vendors describe their capacity differently. To properly compare capacity of a Hadoop appliance, we need to look at how many dedicated Hadoop data nodes there are, the number of drives per data node,…
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