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 open-source, there is no licensing requirement.
If you want to use a hybrid solution, setting up with AWS Lambda can be complex. The startup time of each function can be very slow, causing some delays. AWS Lambda should include support for more languages to make it more competitive with other serverless solutions.
AWS Batch lets you easily and efficiently run hundreds of thousands of batch computing jobs on AWS. When using AWS Batch, there is no need to install or manage batch computing software or server clusters; you can focus mainly on analyzing results and solving problems.
We would like to see AWS Batch provide more documentation and better training on how to use it best. If you are not tech-savvy, this solution may be a bit hard to work with. There is a very big learning curve.
Conclusion:
Both of these are very good compute tools, but they do have some differences.
AWS Lambda sets quotas for the amount of compute and storage resources that you can use to run and store functions. You can learn more about AWS Lambda quotas here.
AWS Batch helps you run batch computing workloads on the AWS cloud. This solution can efficiently provision resources to eliminate capacity restraints and reduce costs and deliver results quickly. AWS Batch does the heavy lifting and helps you run workloads of any scale.
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...
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 open-source, there is no licensing requirement.
If you want to use a hybrid solution, setting up with AWS Lambda can be complex. The startup time of each function can be very slow, causing some delays. AWS Lambda should include support for more languages to make it more competitive with other serverless solutions.
AWS Batch lets you easily and efficiently run hundreds of thousands of batch computing jobs on AWS. When using AWS Batch, there is no need to install or manage batch computing software or server clusters; you can focus mainly on analyzing results and solving problems.
We would like to see AWS Batch provide more documentation and better training on how to use it best. If you are not tech-savvy, this solution may be a bit hard to work with. There is a very big learning curve.
Conclusion:
Both of these are very good compute tools, but they do have some differences.
AWS Lambda sets quotas for the amount of compute and storage resources that you can use to run and store functions. You can learn more about AWS Lambda quotas here.
AWS Batch helps you run batch computing workloads on the AWS cloud. This solution can efficiently provision resources to eliminate capacity restraints and reduce costs and deliver results quickly. AWS Batch does the heavy lifting and helps you run workloads of any scale.