I’m excited about this new productivity solution the nClouds team has created — we’ve made it faster and easier to get started on big data apps with the Quick Start for Amazon EMR by nClouds.
We saw that as our clients were instrumenting their infrastructure and overall business, they were creating enormous volumes of data. To manage this data, and make it simpler to build and deploy analytics apps, there are a number of big data frameworks capable of processing large data sets across many computers.
Apache Hadoop is a popular example of such a framework. It uses algorithms and a component stack to make large-scale batch processing more accessible. However, it can be difficult, time-consuming, and expensive to implement the framework, especially when deploying, configuring, and managing distributed clusters.
We’ve been using Amazon EMR, a managed Hadoop framework that uses the elastic infrastructure of Amazon EC2 and Amazon S3, to make it easy, fast, and cost-effective to distribute data computation across multiple, dynamically-scalable EC2 instances.
If you’re new to Amazon EMR, it essentially enables you to run big data frameworks like Apache Hadoop, Apache Spark, HBase, Presto, and Flink on AWS. You can interact with data in other AWS data stores such as Amazon S3 and Amazon DynamoDB and process it for analytics purposes and business intelligence workloads.
Amazon EMR also securely and reliably handles a broad set of big data use cases, including log analysis, web indexing, data transformations (ETL), machine learning, financial analysis, scientific simulation, and bioinformatics.
We wanted to make it fast and easy to get started with Amazon EMR so we created a Quick Start for Amazon EMR by nClouds. You can get up and running fast with all your use cases, and we’ve made it really easy to use Spot and Dedicated Instance discounts to help you save money.
Go faster and reduce costs — that’s the name of the game:
The Quick Start includes everything you need to get started, including a demo with CloudFormation Template, sample .csv file, pyspark script, and more.
Click to view the Quick Start for Amazon EMR by nClouds.