AWS Batch vs Amazon Elastic Inference comparison

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492 views|404 comparisons
Amazon Web Services (AWS) Logo
7,488 views|7,167 comparisons
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Executive Summary

We performed a comparison between Amazon Elastic Inference and AWS Batch based on real PeerSpot user reviews.

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  • "AWS Batch's pricing is good."
  • "The pricing is very fair."
  • "AWS Batch is a cheap solution."
  • More AWS Batch Pricing and Cost Advice →

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    Top Answer:AWS Lambda is a serverless solution. It doesn’t require any infrastructure, which allows for cost savings. There is no setup process to deal with, as the entire solution is in the cloud. If you use… more »
    Top Answer:AWS Batch manages the execution of computing workload, including job scheduling, provisioning, and scaling.
    Ranking
    12th
    out of 16 in Compute Service
    Views
    492
    Comparisons
    404
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    4th
    out of 16 in Compute Service
    Views
    7,488
    Comparisons
    7,167
    Reviews
    3
    Average Words per Review
    1,179
    Rating
    8.7
    Comparisons
    Also Known As
    Amazon Batch
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    Overview

    Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances or Amazon ECS tasks to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, and ONNX models, with more frameworks coming soon.
    In most deep learning applications, making predictions using a trained model—a process called inference—can drive as much as 90% of the compute costs of the application due to two factors. First, standalone GPU instances are designed for model training and are typically oversized for inference. While training jobs batch process hundreds of data samples in parallel, most inference happens on a single input in real time that consumes only a small amount of GPU compute. Even at peak load, a GPU's compute capacity may not be fully utilized, which is wasteful and costly. Second, different models need different amounts of GPU, CPU, and memory resources. Selecting a GPU instance type that is big enough to satisfy the requirements of the most demanding resource often results in under-utilization of the other resources and high costs.
    Amazon Elastic Inference solves these problems by allowing you to attach just the right amount of GPU-powered inference acceleration to any EC2 or SageMaker instance type or ECS task with no code changes. With Amazon Elastic Inference, you can now choose the instance type that is best suited to the overall CPU and memory needs of your application, and then separately configure the amount of inference acceleration that you need to use resources efficiently and to reduce the cost of running inference.

    AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. AWS Batch dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted. With AWS Batch, there is no need to install and manage batch computing software or server clusters that you use to run your jobs, allowing you to focus on analyzing results and solving problems. AWS Batch plans, schedules, and executes your batch computing workloads across the full range of AWS compute services and features, such as Amazon EC2 and Spot Instances.

    Sample Customers
    Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
    Hess, Expedia, Kelloggs, Philips, HyperTrack
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company19%
    Financial Services Firm15%
    Educational Organization13%
    Comms Service Provider10%
    VISITORS READING REVIEWS
    Financial Services Firm24%
    Computer Software Company13%
    Manufacturing Company6%
    Insurance Company5%
    Company Size
    VISITORS READING REVIEWS
    Small Business22%
    Midsize Enterprise12%
    Large Enterprise67%
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise12%
    Large Enterprise72%
    Buyer's Guide
    Compute Service
    March 2024
    Find out what your peers are saying about Amazon, Apache, Zadara and others in Compute Service. Updated: March 2024.
    765,234 professionals have used our research since 2012.

    Amazon Elastic Inference is ranked 12th in Compute Service while AWS Batch is ranked 4th in Compute Service with 4 reviews. Amazon Elastic Inference is rated 0.0, while AWS Batch is rated 9.0. On the other hand, the top reviewer of AWS Batch writes "User-friendly, good customization and offers exceptional scalability, allowing users to run jobs ranging from 32 cores to over 2,000 cores". Amazon Elastic Inference is most compared with AWS Fargate, AWS Lambda and Amazon EC2 Auto Scaling, whereas AWS Batch is most compared with AWS Lambda, Apache Spark, AWS Fargate and Oracle Compute Cloud Service.

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