Apache Spark vs FME Flow
Apache Spark
spark.apache.orgFME Flow
fme.safe.comSide by side
| Figure | Apache Spark | FME Flow |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | Yes |
| macOS | Yes | — |
| Linux | Yes | Yes |
| iOS | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · ETL Software | 8.3 (#10) | 7.6 (#16) |
| Deployment | Spark documents standalone, Hadoop YARN, and Kubernetes deployment options. | FME Flow can be deployed in cloud, on-premises, hybrid, containerized, and distributed environments. |
| Founded | 2009 | 1993 |
| Integrations | The listed ecosystem includes pandas, TensorFlow, PyTorch, scikit-learn, Apache Kafka, Kubernetes, Delta Lake, and Apache Iceberg. | Safe Software says FME offers over 1,000 application integrations, with additional community-built items available through FME Hub. |
| Purpose | Apache Spark is a unified engine for large-scale data analytics. | FME Flow deploys workflows and powers solutions using automations, no-code web apps, and other tools. |
| Security | Security features such as authentication are not enabled by default, and the documentation says deployments are not secure by default. | Safe Software says it is certified to ISO 27001 and has a SOC 2 Type 2 report; its security page also lists PCI DSS, GDPR, and PIPEDA. |
| Support | The project directs users to mailing lists and community resources for help. | Standard one-to-one customer support is for customers with active maintenance or subscription on supported versions; stated support hours are 8 a.m.–5 p.m. Pacific, Monday through Friday, excluding recognized Canadian holidays. |
Plans
In their own words
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.
FME Flow
FME Flow deploys workflows and data-powered solutions through automation, no-code web apps and related tools. It supports ETL, data replication and synchronization, with instant or event-triggered runs to keep data and applications current. Teams can create no-code web apps for workflow coordination and collaboration, and expose FME-powered services through an OpenAPI interface. Safe Software says FME offers more than 1,000 application integrations, with additional community-built options through FME Hub. Deployment can be cloud, on-premises, hybrid, containerized or distributed. FME Flow Hosted runs on Amazon Web Services, while Safe Software handles server maintenance and backups. Subscriptions include unlimited web users and system connections, with pricing tailored to each client. Listed platforms include API, iOS, Linux, self-hosted, web and Windows. Safe Software, founded in 1993 in Surrey, British Columbia, lists ISO 27001 certification, a SOC 2 Type 2 report, PCI DSS, GDPR and PIPEDA.