Reviewed by Aditya Kumar · Last reviewed 2026-03-24
**Glue**: Serverless Spark; no cluster management; Data Catalog integration; job bookmarks. Suits standard batch ETL, moderate Spark. Cost-effective for variable/infrequent jobs. 15-min DPU minimum—inefficient for very short jobs. **EMR**: Full Spark control; custom configs;...
Glue: Serverless Spark; no cluster management; Data Catalog integration; job bookmarks. Suits standard batch ETL, moderate Spark. Cost-effective for variable/infrequent jobs. 15-min DPU minimum—inefficient for very short jobs. EMR: Full Spark control; custom configs; MLlib, graph. Use when Glue doesn't fit—long-running, custom libs. Scalability: Both auto-scale; Glue per-job; EMR per-cluster. Cost: Glue for sporadic; EMR for steady or custom. Decision: Glue for most pipelines; EMR for ML, graph, or when 15-min minimum hurts.
Pro-Move: 'We use Glue for 45/50 jobs; EMR for 5 ML pipelines—chose based on job profile and 15-min minimum economics.' Red Flag: Using EMR for standard ETL—over-provisioning; Glue is simpler.
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