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Running Hadoop in the Cloud

Running Hadoop in the Cloud

hadoop-logoInternet of Things, Cloud Computing and Big Data are the pioneers of the new world and transformed us toward the ultimate power, which is information. From smart homes to smart cars and smartphones, we are all surrounded by the power of the cloud. For instance, let’s take a look at developers: 54% of them are building robotics apps, 27.4% are building apps in the cloud and 24.7% are using machine learning for development projects. And all this is happening Today!

According to IDC forecast, Big Data and Analytics market will increase from $122 billion in 2015 up to $187 billion in 2019, which means a clear and endless progress. And like any progress, we need to find new ways and solution to cope with it. One of the answers was Hadoop on premise, which seemed the perfect solution for storing and processing data while maintaining a company’s’ competitiveness. However, the maintenance process is a challenging and expensive one. This is how Hadoop-as-a-Service entered the landscape, and Amazon was the first that has offered it as a service.

The best part of HaaS is that all the data is stored and processed in the cloud. Moreover, Hadoop-as-a-service comes with a few extra features and support:

  • Hadoop framework deployment support
  • Security enhanced
  • Customizable dashboards
  • Data transfer between clusters
  • Alternative programming languages

Why run Hadoop in the cloud?

The benefits you get by moving your on-premise Hadoop in the cloud are multiple:

  • Lower innovation costs – Everybody is looking to move all the application and software in the cloud, and Hadoop is one of them. By now, everybody knows that cloud means fewer expenses.
  • Handling batch workloads efficiently – HaaS allows incoming data processing to be scheduled only for the period when the data needs to be compiled.
  • Running closer to the data – Running Hadoop clusters in the same environment where all the data is stored, increases efficiency and reduces data’s migration time from the source to the analytics clusters
  • Simplified operations – It doesn’t require any hardware or infrastructure management   

How to choose the perfect HaaS? Here are a few tips:

  • It has to be self-configured to allow automatic configuration based on workload
  • It should store data in HDFS, avoiding issues related to translating the data stored in other formats into HDFS
  • It should be able to recover from processing failures without restarting the whole process

Bottom line, Hadoop-as-a-Service market will grow nearly 85% annually by 2019, according to Research and Markets, so we will keep bumping into it in the coming years. Would you switch to HaaS?

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