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EduPristine>Blog>Lesser heard Big Data technologies

Lesser heard Big Data technologies

August 26, 2014

When it comes to studying big data technologies it is quite interesting to note that various technologies enable us to do different things with greater efficiency. Due to the wide range of tools and technologies available in the market, we need to smartly pick what type of Big Data technologies are best suited to the purpose at hand. Here we enlist a few of the lesser heard technologies shaping market and defining big data technologies.

The first one to be discussed is Storm and Kafka, these effectively increase the speed of analysis as streams of messages are processed linearly and thousands of these can be reliably handled. Furthermore real time business needs which are generally not catered to are taken care of by this computation system. The roots of this are born from the social networking media where a lot of big data has to be filtered and processed at real time.

Next we look at Drill and Dremel which helps us in addressing the issue of querying. By successfully establishing priority, creating visualization they help in solving ad hoc issues concerning gigantic amounts of data. Since most companies are bent on building real time solutions, and waiting becomes a huge headache this Big Data technology solves most such problems.

Moving on to Gremlin and Giraph, it is an upcoming technology which effectively makes use of graphs which are fundamental to data analysis in many ways. For more reasons than one, graphical analysis is popular in every type of sciences. Computer Networking is best understood by graphs, since graphical analysis provides shortest paths, routes to be taken, traffic analysis and various other parameters all put together in a way that we can make sense of it perfectly well, utilizing very little time indeed. Physics and Biology also find wide usage for graph technology, and this is reciprocated well in the number of scientists using such tools in Big Data Technologies.

So all in all when it comes to shaping Big Data Technologies it is about diversity, utility and speed. The world works on speed at the moment and faster the processing, the smoother the business.

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