{"id":9855,"date":"2020-03-25T21:36:43","date_gmt":"2020-03-25T21:36:43","guid":{"rendered":"https:\/\/blog.uruit.com\/?p=9855"},"modified":"2023-06-26T08:46:58","modified_gmt":"2023-06-26T11:46:58","slug":"big-data-introduction","status":"publish","type":"post","link":"https:\/\/uruit.com\/blog\/big-data-introduction\/","title":{"rendered":"A Brief Introduction to Big Data Applications and Hadoop"},"content":{"rendered":"

Usually, big data applications are one of two types: data at rest and data in motion. The difference between them is the same as the difference between a lake and a river<\/strong><\/span>\u2014<\/span>a lake is a place that contains a lot of water while a river is a place where a lot of water is travelling through.\u00a0<\/span><\/p>\n

For this reason, data at rest applications are often referred to as a data lake while data in motion applications are called data streams or data rivers.\u00a0<\/span><\/p>\n

Fun Fact<\/i><\/b>\u00a0<\/span><\/i><\/p>\n

The “Rio de la plata\u201d, located next to our office in Uruguay, is the widest river in the world, measuring 220km\/140mi wide \ud83d\ude42<\/span><\/i><\/p><\/blockquote>\n

We\u2019re now going to give an overview of the most used technologies and tools for big data, some of the concepts and challenges behind it and a gentle introduction on how to start developing and testing big data applications in a virtualized environment.<\/span><\/p>\n

For this article, we\u2019ll focus mainly on data at rest applications and on the Hadoop ecosystem specifically.<\/span><\/p>\n

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Contents<\/p>\n<\/i><\/a><\/span><\/div>\n