What is the difference between Apache Spark and AWS?

Apache Spark and AWS are not competing products. Spark is an open-source engine for distributed data processing, maintained by the Apache Software Foundation. AWS is a cloud provider that sells the infrastructure and managed services Spark runs on, including Amazon EMR and AWS Glue.

Where does the confusion come from?

The two names show up together constantly in job listings and tutorials, which makes them sound like alternatives to choose between. In practice, "Spark on AWS" just describes where the engine runs. Spark started as a research project at UC Berkeley's AMPLab in 2009 and became a top-level Apache project in 2014, years before AWS built managed services around it. It runs the same way whether the cluster sits on AWS, Google Cloud, Azure, on-premises hardware, or inside a Databricks workspace.

How does AWS actually run Spark?

AWS doesn't build its own version of Spark. Amazon EMR provisions and manages Spark clusters directly. AWS Glue uses Spark under the hood for its ETL jobs, so a Glue job is often a Spark script that AWS schedules and scales. EMR Serverless removes cluster management entirely by auto-scaling Spark executors per job. Each of these packages Spark; none of them replaces it.

For hiring, this distinction matters because "AWS experience" and "Spark experience" test different skills: cluster and IAM configuration on one side, Spark SQL and DataFrame tuning on the other. A candidate can be strong in one and thin in the other.

Published at: 2026-08-07