4 Reasons Why Hadoop is Heading for the Clouds
By Afia Ahmad
With most businesses being completely data-centric, cloud computing and Big Data have been on the radar of businesses for several years now. Running Hadoop on the cloud is not a new idea. Over the past year, there have been several developments in this area of new projects relating to Hadoop running on cloud computing.
Hadoop is bound to become a necessity for organizations due to the immense number of applications relying on large data sets. Hadoop in a cloud allows for speedy completion of jobs as usage of the cloud enables parallel processing across multiple servers.
Some of the reasons why Hadoop works better in the cloud:
1. Scalable and flexible
Businesses are constantly expanding. Business expansion usually requires more computing power than the capacity of the current system. Now, that would not only take time, but also be an expensive process. With a Cloud system, however, businesses can scale to the size as required, thereby saving time and money. Transferring data would also be a tedious and costly task. However, in a cloud environment, that would not be required and the data would still be accessible anywhere.
Maintaining and developing an in-house data centre is not something every company can afford. Smaller companies that cannot afford the investment for the expensive hardware can benefit from the cost-efficacy of a cloud environment. Small businesses can use public clouds and only pay for what they use. Large businesses can use private clouds to replace in-house data centres, and public clouds for short term projects without having to expand their in-house system.
3. Simplification of innovation
For companies that are still testing out Hadoop, an investment in data centers may not make sense. Usage of cloud environment, however, allows organizations to lower the cost of innovation and increase the investment into research and other beneficial innovation programs.
4. Efficacy of batch workloads
Hadoop is a batch-oriented system, which means that data is collected and fed into the analytics application a few times a day in varying schedules to extract the output. Hadoop that runs on the physical data centres have to be on throughout this time frame thus consuming resources and proving to be expensive. The cloud environment, however, allows you to pay for what you use, thereby not only making efficient use of resources, but also reducing the cost to the company.
Completely moving Hadoop into the cloud may not, however, be the best option for some organizations. A hybrid structure that makes the best of cloud computing while having a physical data centre would fare well for larger organizations. However, the potential for increased efficiency and cost savings definitely makes the cloud for Hadoop an interesting proposition. If you feel passionate about Big Data, and think that you can contribute to this ever-developing field, you could always expand your skillset through a Hadoop tutorial or a Big Data analytics course.
Of course, a world-class option is Manipal ProLearn, where you can jump on the bandwagon and undergo Big Data training or Hadoop training and be a part of the niche sector that every organization is trying to bank on!