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Imagine a case where you have 10000 random points in a two-dimensional space, and you need to write a program that detects points in a given rectangular area.

 

Let’s visualize this for a better understanding of the problem.

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With the recent arrival of various search servers and analytics engines, the process to store, search and analyze huge volumes of data in real time has become easier. Elasticsearch is one such search and analytics engine. It is a highly scalable, open-source full-text search and analytics engine suitable for applications that require complex search features. (more…)

 

MySQL vs MongoDB: A comparison on relational and non-relational databases

 

When we talk about databases, the name MongoDB might be unfamiliar at least to some of us. MongoDB is a relatively new player when compared to other established databases such as MySQL and PostgreSQL.

 

MySQL is the most popular database in the world because of its speed, robustness, and ease of use. MongoDB, although not as popular as MySQL, is gaining traction due to its performance. It also supports a flexible data model that delivers ease in building apps in an agile way, where the schema may not be known upfront. (more…)

Data mining does not stop with data warehousing, big data analytics tools and visualization for IT decision-makers, who are equally concerned with business metrics such as machine requirement, performance, cost, human resources and ROI. Predictably, reducing IT cost figures as a recurring motive among companies doing big data. Intel’s research highlight that 20 percent of firms aim at lowering IT cost, making it the third most important driving factor in big data investment.

 

Hadoop and assorted Apache open source projects have taken the big data space by storm as a cost effective alternative. As Doug Cutting of Hadoop fame puts it “Competing against open source is a tough game—everybody else is collaborating on it; the cost is zero. It’s easier to join than to fight.”

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