Amazon Elastic MapReduce Pricing

With Amazon EMR you only pay for what you use. Amazon EMR pricing is in addition to pricing for EC2 and S3. We charge less where our costs are less, and your cost will depend on the number and type of Amazon EC2 Instances in your job flow and the amount of time it is running.

You are charged per-second from the time your cluster starts until it is terminated, with a one-minute minimum.

Amazon S3 is billed separately. (Many customers store their input and output data in S3; others store all of the data locally on HDFS.) The more data you store, the lower the monthly price per GB.

With Amazon EMR you only pay for what you use. Amazon EMR pricing is in addition to pricing for EC2 and S3. We charge less where our costs are less, and your cost will depend on the number and type of Amazon EC2 Instances in your job flow and the amount of time it is running.

You are charged per-second from the time your cluster starts until it is terminated, with a one-minute minimum.

Amazon S3 is billed separately. (Many customers store their input and output data in S3; others store all of the data locally on HDFS.) The more data you store, the lower the monthly price per GB.

This pricing is for Amazon EMR on Amazon EKS clusters.

The Amazon EMR price is in addition to the Amazon EKS pricing or any other services used with Amazon EKS. You can run EKS on Amazon Web Services using either EC2 or Amazon Fargate. If you are using Amazon EC2 (including with EKS managed node groups), you pay for Amazon Web Services resources (e.g., EC2 instances or Amazon EBS volumes) you create to run your Kubernetes worker nodes. See detailed pricing information on the Amazon EC2 pricing page. If you are using Amazon Fargate, pricing is calculated based on the vCPU and memory resources used from the time you start to download your container image until the Amazon EKS pod terminates, rounded up to the nearest second. A minimum charge of 1 minute applies. See detailed pricing information on the Amazon Fargate pricing page.

Amazon EMR pricing on EKS is calculated based on the vCPU and memory resources used from the time you start to download your EMR application image until the Amazon EKS Pod terminates, rounded up to the nearest second. Pricing is based on requested vCPU and memory resources for the Task or Pod. 

Pricing Example

Pricing based on China (Beijing) Region pricing.

Suppose you are running an EMR-Spark application deployed on Amazon EKS. In this case, EKS gets its compute capacity using r5.2xlarge EC2 instances (8 vCPU, 64 GB RAM). Let’s assume that the EKS cluster has 100 nodes, totaling 800 vCPU, and 6400GB of total memory. Let’s assume that that application utilizes 100 VCPUs and 300GB of memory for 30 minutes.

Total EMR uplift charges for the job:

• Total Uplift on vCPU = (100 * ¥0.0902975 * 0.5) = (number of vCPU * per vCPU-hours rate * job runtime in hour) = ¥4.51
• Total Uplift on memory = (300 * ¥0.00995675 * 0.5) = (amount of memory used * per GB-hours rate * job runtime in hour) = ¥1.49
• Total EMR Uplift for the EMR job = ¥6.01

Additional Costs

You pay ¥0.688 per hour for each Amazon EKS cluster that you create. You can use a single Amazon EKS cluster to run multiple applications by taking advantage of Kubernetes namespaces and IAM security policies. You can run EKS on Amazon Web Services using either Amazon EC2 or Amazon Fargate.

If you are using EC2 (including with EKS managed node groups), you pay for Amazon Web Services resources (e.g., EC2 instances or EBS volumes) you create to run your Kubernetes worker nodes. You only pay for what you use, as you use it. There are no minimum fees and no upfront commitments. See detailed pricing information on the Amazon EC2 pricing page.

If you are using Amazon Fargate, pricing is calculated based on the vCPU and memory resources used from the time you start to download your container image until the Amazon EKS pod terminates, rounded up to the nearest second. A minimum charge of 1 minute applies. See detailed pricing information on the Amazon Fargate pricing page.