AWS Batch vs AWS Lambda: What are the differences?

AWS Batch and AWS Lambda are both services offered by Amazon Web Services (AWS) that enable developers to run and manage their applications at scale. However, there are some key differences between the two:

1. Scaling and Control: AWS Batch provides fine-grained control over the scaling and management of your batch computing workloads. It allows you to set up and manage queues, define job dependencies, and control batch scheduling. On the other hand, AWS Lambda automatically scales your application to handle incoming requests, without requiring manual management or configuration.

2. Pricing Model: AWS Batch follows a pay-as-you-go pricing model, where you are charged based on the number of vCPUs and memory resources used by your batch compute environments. In contrast, AWS Lambda follows a metered pricing model, where you are billed based on the number of requests and the duration of each request invocation.

3. Compute Environment: AWS Batch allows you to define and manage your own compute environments, where you have control over the type and capacity of the underlying EC2 instances used for batch processing. On the other hand, AWS Lambda abstracts the compute environment and automatically manages the infrastructure, allowing you to focus on writing code without worrying about the underlying resources.

4. Execution Limits: AWS Batch allows you to run long-running processes, where each job can run for hours or even days if needed. This is particularly useful for scientific and batch processing workloads. On the other hand, AWS Lambda has a maximum execution duration limit of five minutes, which makes it most suitable for short-lived tasks or event-driven applications.

5. Integration with Services: AWS Batch can be easily integrated with other AWS services such as Amazon S3, Amazon DynamoDB, and AWS Step Functions. This allows you to build complex workflows and process large amounts of data using batch processing. AWS Lambda also has integrations with various AWS services, but its main strength lies in its ability to respond to events and trigger serverless functions in response to actions from other services.

6. Dependencies and Language Support: AWS Batch supports running applications written in any programming language as long as it can be containerized. This gives you the flexibility to use your preferred programming language. On the other hand, AWS Lambda supports a wider range of programming languages out of the box, including Node.js, Java, Python, Ruby, C#, PowerShell, and Go. It also allows you to include external libraries and dependencies in your function code.

In summary, AWS Batch provides fine-grained control over batch processing workloads, while AWS Lambda offers automatic scaling and event-based execution for serverless functions.