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Amazon Web Services (AWS) Logo
6,770 views|6,477 comparisons
100% willing to recommend
Amazon Web Services (AWS) Logo
11,937 views|8,175 comparisons
94% willing to recommend
Comparison Buyer's Guide
Executive Summary
Updated on Mar 6, 2024

We compared AWS Lambda and AWS Batch based on our user's reviews in several parameters.

Based on user feedback, AWS Lambda is praised for its scalability, ease of use, and cost-effectiveness. Users appreciate the support provided and the significant cost savings achieved. On the other hand, AWS Batch is valued for its optimization of batch computing workloads, seamless integration with AWS services, and reliability. Users suggest enhancements in interface, troubleshooting resources, and integrations for better user experience.

Features: AWS Lambda is highly valued for its scaling capabilities and cost-effective pricing model. It offers quick deployment and supports multiple programming languages. In contrast, AWS Batch excels in managing and optimizing batch computing workloads, seamlessly integrating with other AWS services. It also offers high scalability, a user-friendly interface for job scheduling and resource management, and dynamic resource allocation. Data security and reliability are also praised.

Pricing and ROI: The setup cost for AWS Lambda is minimal and easy to navigate, while AWS Batch offers a straightforward and hassle-free setup process. Customers have found the pricing of both products to be fair and reasonable, with AWS Batch providing flexibility and scalability in licensing options., AWS Lambda has been highly praised for its cost-effectiveness and efficiency, resulting in improved productivity, reduced operational costs, and increased scalability. Users particularly appreciated the pay-as-you-go pricing model and optimized returns on investment. On the other hand, feedback on the ROI from AWS Batch seems to be satisfactory.

Room for Improvement: AWS Lambda users have identified the need for faster deployment, reduced cold start times, improved resource allocation management, and enhanced debugging capabilities. In contrast, AWS Batch users have requested a refined interface, streamlined workflow, improved documentation, comprehensive troubleshooting resources, enhanced monitoring capabilities, and additional integrations with other AWS services.

Deployment and customer support: Based on user feedback, AWS Lambda and AWS Batch have different experiences regarding the duration required for deployment, setup, and implementation. While users of AWS Lambda emphasize the importance of considering the context in which these terms are used, users of AWS Batch mention that the duration can vary and suggest evaluating deployment and setup separately in some cases., Users have praised the customer service of AWS Lambda for their responsiveness, expertise, and helpfulness. AWS Batch also receives positive remarks, with users highlighting the effectiveness of their support team in addressing queries and issues. Both offer prompt and reliable assistance.

The summary above is based on 39 interviews we conducted recently with AWS Lambda and AWS Batch users. To access the review's full transcripts, download our report.

To learn more, read our detailed AWS Batch vs. AWS Lambda Report (Updated: May 2024).
772,422 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"There is one other feature in confirmation or call confirmation where you can have templates of what you want to do and just modify those to customize it to your needs. And these templates basically make it a lot easier for you to get started.""We can easily integrate AWS container images into the product.""AWS Batch's deployment was easy.""AWS Batch manages the execution of computing workload, including job scheduling, provisioning, and scaling."

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"Because AWS Lambda is serverless, server configuration is not required, and we can run it directly anywhere.""The initial setup of AWS Lambda is very straightforward and quick.""The most valuable feature is that it scans the cloud system and if they are any security anomalies it triggers an email.""Thanks to this solution, we do not need to worry about hardware or resource utilization. It saves us time.""What I like best about AWS Lambda is that it's feature-rich, and I appreciate that. I also like that it's stable and supports many languages.""The solution is designed very well. You don't need to keep a server up. You just need some router to route your API request and Lambda provides a very well-designed feature to process the request.""AWS Lambda is interlinked with CloudWatch. When we have any errors we can directly go there and check the CloudWatch logs. Additionally, we can run it very fast and we can increase the RAM size and other components.""Some of the most valuable features are that it's easy to install and use. The performance is also good."

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Cons
"The main drawback to using AWS Batch would be the cost. It will be more expensive in some cases than using an HPC. It's more amenable to cases where you have spot requirements.""AWS Batch needs to improve its documentation.""The solution should include better and seamless integration with other AWS services, like Amazon S3 data storage and EC2 compute resources.""When we run a lot of batch jobs, the UI must show the history."

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"AWS Lambda should support additional languages.""AWS Lambda could be improved with better stability.""The execution time could be better. One of the major limitations is the time period because it doesn't give you more than seven minutes. So, before thinking about Lambda, you should think through your use case and ensure it's a good fit. Otherwise, you can use batch, step functions, or other methods. Reports and the monitoring board could also be improved in terms of alerts. The threshold alerts are there but can be improved. It takes some time to get used to these methods and get the hang of them.""The automation with other Amazon products could be better.""Lambda could be improved in the sense that some of the things done with Lambda function take some time. So the performance could be better and faster.""Amazon doesn't have enough local support based in our country.""It would be ideal if we could use the solution across different platforms.""We need to better understand Lambda for different scenarios. We need some joint effort between Amazon and the users to have the users identify how they can really leverage Lambda. It's not about Lambda itself; it's about the practice, the guidance. There needs to be very good documentation. From the user perspective, what exists now is not always enough."

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

  • "AWS is slightly more expensive than Azure."
  • "Its pricing is on the higher side."
  • "The price of the solution is reasonable and it is a pay-per-use model. It is very good for cost optimization."
  • "The cost is based on runtime."
  • "The fees are volume-based."
  • "AWS Lambda is inexpensive."
  • "Lambda is a good and cheap solution and I would recommend it to those without a huge payload."
  • "For licensing, we pay a yearly subscription."
  • More AWS Lambda Pricing and Cost Advice →

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    Questions from the Community
    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.
    Top Answer:The tool scales automatically based on the number of incoming requests.
    Top Answer:We only need to pay for the compute time our code consumes. The solution does not cost much.
    Top Answer:We must at least know the basics of languages like Python or Java to implement automatic processes and daily schedules. We must learn the Lambda function and the languages to use the tool.
    Ranking
    4th
    out of 16 in Compute Service
    Views
    6,770
    Comparisons
    6,477
    Reviews
    4
    Average Words per Review
    973
    Rating
    9.0
    1st
    out of 16 in Compute Service
    Views
    11,937
    Comparisons
    8,175
    Reviews
    39
    Average Words per Review
    391
    Rating
    8.6
    Comparisons
    Also Known As
    Amazon Batch
    Learn More
    Overview

    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.

    AWS Lambda is a compute service that lets you run code without provisioning or managing servers. AWS Lambda executes your code only when needed and scales automatically, from a few requests per day to thousands per second. You pay only for the compute time you consume - there is no charge when your code is not running. With AWS Lambda, you can run code for virtually any type of application or backend service - all with zero administration. AWS Lambda runs your code on a high-availability compute infrastructure and performs all of the administration of the compute resources, including server and operating system maintenance, capacity provisioning and automatic scaling, code monitoring and logging. All you need to do is supply your code in one of the languages that AWS Lambda supports (currently Node.js, Java, C# and Python).

    You can use AWS Lambda to run your code in response to events, such as changes to data in an Amazon S3 bucket or an Amazon DynamoDB table; to run your code in response to HTTP requests using Amazon API Gateway; or invoke your code using API calls made using AWS SDKs. With these capabilities, you can use Lambda to easily build data processing triggers for AWS services like Amazon S3 and Amazon DynamoDB process streaming data stored in Amazon Kinesis, or create your own back end that operates at AWS scale, performance, and security.

    Sample Customers
    Hess, Expedia, Kelloggs, Philips, HyperTrack
    Netflix
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm26%
    Computer Software Company13%
    Manufacturing Company6%
    Educational Organization5%
    REVIEWERS
    Financial Services Firm24%
    Computer Software Company21%
    Non Profit5%
    Educational Organization5%
    VISITORS READING REVIEWS
    Educational Organization48%
    Financial Services Firm13%
    Computer Software Company8%
    Manufacturing Company4%
    Company Size
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise12%
    Large Enterprise72%
    REVIEWERS
    Small Business38%
    Midsize Enterprise15%
    Large Enterprise47%
    VISITORS READING REVIEWS
    Small Business10%
    Midsize Enterprise52%
    Large Enterprise38%
    Buyer's Guide
    AWS Batch vs. AWS Lambda
    May 2024
    Find out what your peers are saying about AWS Batch vs. AWS Lambda and other solutions. Updated: May 2024.
    772,422 professionals have used our research since 2012.

    AWS Batch is ranked 4th in Compute Service with 4 reviews while AWS Lambda is ranked 1st in Compute Service with 70 reviews. AWS Batch is rated 9.0, while AWS Lambda is rated 8.6. 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". On the other hand, the top reviewer of AWS Lambda writes "An easily scalable solution with a variety of use cases and valuable event-based triggers". AWS Batch is most compared with Apache Spark, AWS Fargate, Oracle Compute Cloud Service, Amazon EC2 Auto Scaling and Amazon EC2, whereas AWS Lambda is most compared with Amazon EC2 Auto Scaling, Apache NiFi, Apache Spark, AWS Fargate and Google Cloud Dataflow. See our AWS Batch vs. AWS Lambda report.

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    We monitor all Compute Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.