If you want to rapidly and securely process large amounts of data, Amazon Elastic MapReduce (Amazon EMR) can do that for you. Using Apache Hadoop, Apache Spark, and Presto, EMR lets you process big data in an easy and cost-effective way.
Thanks to a new enhancement, you can now use EMR with Amazon EBS volumes to raise your local storage for each of your instances.
EMR typically uses the Hadoop Distributed Files System to store files when processing data using its own file system. EBS increases this storage amount, which helps greatly if you require a larger amount of local storage than what your instance can give. Since you can customize exactly how much storage you need, you can save on costs in the long run.
It also helps if you plan on using new instance types, such as M4, C4, and R3, which require more storage than the other EC2 types.
On that note, you can now launch EMR clusters with M4 and C4 instances in the regions they are currently available in. These instances provide the highest level of performance available on AWS EC2 (M4 uses a custom Intel eon E5-2673 v3 and C4 uses Intel Xeon E5-2666 v3).
You can check out the Amazon EMR pricing guide for additional information. And if you are interested in implementing a big data processing strategy for your enterprise, call us now at PolarSeven for an estimate.