What is the Difference Between AWS Batch and Lambda?

Data scientists and engineers can use machine learning training models to perform big data analytics. On the other hand, developers need to build the applications by writing the code for the back end of the software. All these tasks can be done on the cloud using the AWS platform that allows us to access services belonging to the computing domain.

This guide will explain the differences between AWS Batch and Lambda.

What is AWS Batch?

AWS Batch enabled data scientists, engineers, developers, etc. to efficiently perform thousands of batch computing jobs in AWS. This service carries some of the largest workloads ever run on the cloud. In order to work on Batch, the user needs to interact with AWS Batch API service endpoints to specify or submit jobs/ work items:

Features of AWS Batch

Important features of the AWS batch are mentioned below:

  • AWS Batch is a fully managed service as the user needs to specify the basic resource parameters like GPU, CPU, Memory, etc. and the rest will be managed by the service.
  • It interacts with other AWS services like S3 to get the data from its bucket over the cloud.
  • AWS Batch will use to run thousands of batches and uses appropriate machine learning tools to predict the future:

What is AWS Lambda?

Developers prefer to build responsive applications/software for their consumers to get a better response with less latency and downtime. AWS Lambda allows them to build, run, and deploy code for their software and then attach triggers, layers, etc. All this in a serverless service on the cloud using AWS lambda which means that the developers don’t have to worry about managing their applications:

Features of Lambda

Essential features of AWS Lambda are written below:

  • Lambda is a compute service to run backend codes in response to events like object uploads to the S3 bucket, updates to the RDS database, etc.
  • Once the code is uploaded to lambda, it automatically manages scalability, patching, and administration of the infrastructure.
  • It allows the user to create environments for multiple programming languages to test and deploy their code on the cloud:

Lambda Vs. Batch

AWS Batch is a managed service that allows the user to handle big data and run batch-computing jobs/ workloads. While AWS Lambda is a serverless computing service to create backend codes, test, and deploy event-driven tasks. Both of these services belong to the computing domain and perform their tasks on the cloud.

That’s all about the differences between AWS Batch and Lambda.


To sum up, the Lambda and Batch services are somehow different from each other in their working and jobs on the AWS cloud. Lambda is used to create environments for different programming languages to build backend code for the applications. Whereas, Batch is a managed service to handle huge amounts of batch computing jobs using Big data analytics tools. This guide has explained the differences between AWS Batch and Lambda.

About the author

Talha Mahmood

As a technical author, I am eager to learn about writing and technology. I have a degree in computer science which gives me a deep understanding of technical concepts and the ability to communicate them to a variety of audiences effectively.