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 manages the execution of computing workload, including job scheduling, provisioning, and scaling."
"AWS Batch's deployment was easy."
"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."
"The utilization of containers is particularly beneficial in overcoming the size limitations imposed on Lambda functions which not only allows us to work around these constraints but also contributes to the improvement and maintenance of our code."
"It is easy to use."
"The most valuable feature is that it scans the cloud system and if they are any security anomalies it triggers an email."
"Lambda being serverless is a great feature that is appropriate for our use cases."
"AWS Lambda has improved our productivity and functionality."
"The most valuable feature of AWS Lambda, from a conceptual point, is its functions. For example, it's mathematical templates into which you can write, and create your solution. You write small pieces of a solution under given parameters."
"We use AWS Lambda because it provides a solution for our needs without requiring us to manage our infrastructure. With the tool, we only pay for the resources we use. Additionally, it is straightforward to implement and integrates with other services like API Gateway."
"Lambda has improved our organization by making it possible to transform data."
"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."
"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."
"The metrics and reporting for this solution could be improved."
"What could be improved in AWS Lambda is a tricky question because I base the area for improvement on a specific matrix, for example, latency, so I'm still determining if I can be the judge on that. However, room for improvement could be when you're using AWS Lambda as a backend, it can be challenging to use it for monitoring. Monitoring is critical in development, and I don't have much expertise in the area, but you can use other services such as Xray. I found that monitoring on AWS Lambda is a challenge. The tool needs better monitoring. Another area for improvement in AWS Lambda is the cold start, where it takes some time to invoke a function the first time, but after that, invoking it becomes swift. Still, there's room for improvement in that AWS Lambda process. In the next release of AWS Lambda, I'd like AWS to improve monitoring so that I can monitor codes better."
"We don't have the inbuilt modules in AWS Lambda. If more modules were built into or integrated with AWS Lambda, that would help developers to code."
"AWS Lambda should support additional languages."
"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."
"It can be a bit difficult to switch between accounts when creating services for customers."
"Lambda can only be used in one account; there's no possibility to utilize it in another account."
"There is room for improvement in user-friendliness. When comparing this solution to others it is not as user-friendly."
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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