Why Hadoop still make sense

 

Reasons Hadoop still make sense

Hadoop has moved to the cloud now. As the widespread benefits are for everyone to see, we will see how it enhances the power of Hadoop.

• Lowering the cost of innovation

Running Hadoop on the cloud makes sense for relevant reasons as performing any other software contributing on the cloud. 

Companies are still testing the waters with Hadoop, the less capacity investment in the cloud is a no-brainer. 

The cloud plays an important role in making sense for a quick, one-time help case including big data computing.

• Procuring large-scale resources quickly

The point above of quick resource procurement needs some elaboration. 

Hadoop platform was inspired by the vision of linear storage and compute using commodity hardware a reality. 

On internet google, who always managed at web-scale, they know that there will be a demand for running on more hardware resources. 

Hardware had to be acquired on their own.

• Handling Batch Workloads Efficiently

Hadoop is a batch-oriented system, where you can schedule jobs and have an incoming data feed. 

Enterprises are collecting activity data from web server logs and consume this collected data into an analytic function on the Hadoop.

The capacity to compute resources of a Hadoop cluster varies based on the timings of these scheduled runs or rate of incoming data.  

A fixed capacity Hadoop cluster built on physical machines is always on whether it is used or not – consuming power, leased space, etc. and incurring a cost.

• Handling Variable Resource Requirements

Not all Hadoop jobs are created equal. 

Some Hadoop jobs require more computer resources, some of them needs more memory, and some others demand a lot of I/O bandwidth. 

Normally, a physical Hadoop cluster is built of homogeneous machines, usually, they are large enough to handle the biggest work.

• Running Closer to the Data

Today businesses are moving their services to the cloud, it follows that data starts living on the cloud. 

• Simplifying Hadoop Operations

As the cluster merger happens in the business, there is one thing which gets lost is the segregation of resources for different sets of customers. 

As all of the client's jobs get grouped up in a shared cluster, the authority of the cluster gets started to deal with multi-tenancy problems such as clients jobs interfering with each other, varied security constraints etc.

Conclusion:

It is said that the next decade will be going to be dominated by Big-data wherein all the companies will be using the data available to them to learn about their company’s ecosystem and improving fallback.

Learn Big Data with ETLHive.