Apache Flink vs Apache Spark
Apache Flink
flink.apache.orgApache Spark
spark.apache.orgSide by side
| Figure | Apache Flink | Apache Spark |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Streaming Analytics Software | 8.0 (#7) | 8.1 (#5) |
| Spec score · Stream Analytics Software | 8.1 (#8) | 8.2 (#7) |
| Spec score · Stream Processing Software | 8.1 (#8) | 8.2 (#7) |
| Spec score · Big Data Analytics Software | 8.0 (#14) | 8.1 (#13) |
| Integrations | Separately released connectors listed on the downloads page include AWS, Cassandra, Elasticsearch, Google Cloud PubSub, HBase, Hive, JDBC, Kafka, MongoDB, OpenSearch, Prometheus, Pulsar, and RabbitMQ. | The listed ecosystem includes pandas, TensorFlow, PyTorch, scikit-learn, Apache Kafka, Kubernetes, Delta Lake, and Apache Iceberg. |
Plans
In their own words
Apache Flink
Apache Flink is a free, self-hosted framework and distributed processing engine for stateful computations over unbounded and bounded data streams. It supports event-driven applications, stream and batch analytics, and data pipelines and ETL. Listed correctness features include exactly-once state consistency, event-time processing and late-data handling. APIs include SQL for stream and batch data, DataStream and ProcessFunction for time and state. Operational capabilities cover flexible deployment, high availability, savepoints, scale-out architecture, very large state and incremental checkpoints. The project lists low latency, high throughput and in-memory computing. Flink runs in common cluster environments; for Kubernetes, the Kubernetes Operator is identified as the standard deployment mechanism. Connectors include AWS, Cassandra, Elasticsearch, Google Cloud PubSub, HBase, Hive, JDBC, Kafka, MongoDB, OpenSearch, Prometheus, Pulsar and RabbitMQ. Security requires configuration because SSL/TLS, REST authentication and SQL Gateway authentication are disabled by default. It is available at free under Apache License v2.
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.