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.
"AWS Batch's deployment was easy."
"AWS Batch manages the execution of computing workload, including job scheduling, provisioning, and scaling."
"We can easily integrate AWS container images into the product."
"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."
"The main features of this solution are the ability to integrate multiple AWS applications or external applications very quickly and organize all of them. Additionally, it is easy to use and you can run various programming languages, such as Python, Go, and Java."
"I think the most valuable feature is the agility of the solution."
"Because AWS Lambda is serverless, server configuration is not required, and we can run it directly anywhere."
"It's also suitable for companies of any size. For example, we're a large enterprise, and we've used Lambda without any problems in the last 10 months."
"The ease and speed of developing the services using any available language is the most valuable feature."
"Lambda is the preferred compute option because of on-demand cost. We don't have to provision any hardware beforehand. We don't have to provision the capacity required for the services because it is serverless."
"The most valuable features are event-based triggers. They're really good for a reactive style when you want things to happen as soon as something else happens."
"The most valuable feature of this solution is the API Gateway."
"AWS Batch needs to improve its documentation."
"When we run a lot of batch jobs, the UI must show the history."
"The solution should include better and seamless integration with other AWS services, like Amazon S3 data storage and EC2 compute resources."
"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."
"There are sometimes issues following an update."
"The metrics and reporting for this solution could be improved."
"I would like the layers to have a bigger volume. I would like to be able to add more. I don't want to be limited by the layer."
"AWS Lambda has some size limitations in the code line, you can't do a couple of functions to do the job."
"If it is a specific ETL process or a long-term one, then AWS Lambda is not a good option."
"Its price should be improved. Its pricing is on the higher side. I am not sure if it currently supports the Go language. If it doesn't support the Go language, they can introduce it."
"I have seen some drawbacks with certain integrations."
"AWS Lambda could be improved by increasing the size of the payload. Also, sometimes Lambda doesn't implement well for bigger solutions."
AWS Batch is ranked 3rd 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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