Can we replace a Lambda function with Glue?

AWS Glue and AWS Lambda serve different purposes, so a direct replacement depends on the use case. Glue is a managed ETL service that runs Apache Spark jobs, handles schema discovery, job scheduling, and provides a visual interface for building pipelines. It is ideal for large‑scale data transformations, data cataloging, and scheduled batch jobs. Lambda, on the other hand, is a serverless compute service that runs short, event‑driven functions with a maximum execution time of 15 minutes and limited memory. If your Lambda function performs a simple transformation on a small dataset triggered by an event (e.g., an S3 upload), you can replace it with a Glue job by creating a Glue script that reads the file, processes it, and writes the result. However, Glue introduces overhead: you need to set up a Glue job, manage IAM roles, and pay for the Spark cluster time. For very small, low‑latency tasks, Lambda is cheaper and faster. For complex, large‑scale ETL, Glue is more efficient. Therefore, you can replace a Lambda with Glue when the job requires Spark’s distributed processing, schema management, or scheduled execution, but for lightweight, event‑driven logic Lambda remains the better choice.