Can we replace a Glue function with a Lambda function?

Replacing a Glue job with a Lambda function is possible but depends on the job’s complexity and data volume. Glue is designed for large‑scale ETL using Spark; it handles distributed processing, automatic scaling, and provides a data catalog. Lambda is limited to 15‑minute execution, 10 GB RAM, and is event‑driven. If the Glue job performs a simple transformation on a small dataset (e.g., a few megabytes) triggered by an event like an S3 upload or DynamoDB stream, you can rewrite the logic as a Lambda function that reads the data, processes it in memory, and writes the result back. This can reduce cost and latency for lightweight tasks. However, for jobs that require complex transformations, large data volumes, or scheduled batch processing, Glue’s managed Spark environment is more efficient. Additionally, Glue automatically handles schema discovery and job monitoring, features that would need to be built manually in Lambda. In summary, replace Glue with Lambda only when the job is small, event‑driven, and fits within Lambda’s resource limits; otherwise, Glue remains the appropriate choice.