Amazon Managed Service for Apache Flink vs Apache Spark
Amazon Managed Service for Apache Flink
aws.amazon.com
Apache Spark
spark.apache.orgSide by side
| Figure | Amazon Managed Service for Apache Flink | Apache Spark |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 1 |
| Spec score · Streaming Analytics Software | 7.5 (#15) | 8.1 (#5) |
| Spec score · Stream Analytics Software | 7.5 (#17) | 8.2 (#7) |
| Spec score · Stream Processing Software | 7.5 (#17) | 8.2 (#7) |
| Integrations | Listed integrations include Amazon S3, Amazon MSK, Amazon OpenSearch Service, DynamoDB, Kinesis Data Streams, Kinesis Data Firehose, CloudWatch, and AWS Glue Schema Registry. | The listed ecosystem includes pandas, TensorFlow, PyTorch, scikit-learn, Apache Kafka, Kubernetes, Delta Lake, and Apache Iceberg. |
| Purpose | The service runs Apache Flink applications to transform and analyze streaming data in real time. | Apache Spark is a unified engine for large-scale data analytics. |
| Security | Data at rest and in transit is encrypted in the service, and AWS describes security as a shared responsibility between AWS and the customer. | Security features such as authentication are not enabled by default, and the documentation says deployments are not secure by default. |
Plans
Amazon Managed Service for Apache Flink
- Usage-based pricingPrice not published
In their own words
Amazon Managed Service for Apache Flink
Amazon Managed Service for Apache Flink has no write-up on Specifiction yet; its figures are above.
Apache Spark
Apache Spark is a free, open-source engine for large-scale data analytics. It processes batches and real-time streams using Python, SQL, Scala, Java, or R. Spark SQL runs distributed ANSI SQL queries on structured tables and unstructured data such as JSON or images; MLlib provides machine-learning algorithms for local use or cluster scale. The project also describes exploratory analysis on petabyte-scale data without downsampling. Listed ecosystem components include pandas, TensorFlow, PyTorch, scikit-learn, Apache Kafka, Kubernetes, Delta Lake, and Apache Iceberg. Deployment options include standalone, Hadoop YARN, and Kubernetes. Spark runs on Windows and UNIX-like systems, including Linux and macOS, when a supported Java version is available. The 4.2.0 documentation lists Java 17, 21, or 25, Scala 2.13, Python 3.10+, and R 4.0+ (deprecated). Spark Connect separates client applications from clusters for remote access. Security is not enabled by default; Spark supports TLS for RPC connections and encryption of temporary local-disk data. The project is licensed under Apache License, Version 2.0.