AWS Glue and Amazon EMR are both used for big data processing, but AWS Glue is a managed ETL service, while EMR is a scalable cluster-based data processing platform. Glue is serverless and optimized for ETL workflows, whereas EMR supports distributed processing frameworks like Spark, Hadoop, and Presto.
Key Differences: AWS Glue vs. EMR
Purpose – Glue is for ETL automation; EMR is for large-scale data analytics.
Serverless vs. Cluster-based – Glue is fully serverless, while EMR requires cluster setup.
Ease of Use – Glue has pre-built transformations, making it easier for ETL; EMR requires custom configurations.
Performance – EMR is more powerful for advanced analytics, while Glue is optimized for simpler ETL tasks.
Cost Model – Glue charges per ETL job execution, while EMR pricing depends on cluster size and usage.
Which One Should You Choose?
Choose AWS Glue if:
You need a fully managed ETL service.
Your primary task is transforming and moving structured data.
You want automation and minimal setup.
Choose EMR if:
You need scalable big data processing with Spark, Hadoop, or Presto.
You work with large-scale unstructured data.
You require advanced machine learning or data transformation.
Ivan Janjić
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Stefan Mićić
Machine Learning Developer and Data Engineer
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Aleksa Stevic
Full-Stack Developer
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Nemanja Milićević
Data Scientist
Darko Simic
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Luka Patarcic
Technical Lead
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