Apache Spark vs Feldera
Apache Spark
spark.apache.orgFeldera
feldera.comSide by side
| Figure | Apache Spark | Feldera |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 2 |
| Spec score · Streaming Analytics Software | 8.1 (#5) | 7.8 (#12) |
| Spec score · Stream Processing Software | 8.2 (#7) | 7.8 (#14) |
| Deployment | Spark documents standalone, Hadoop YARN, and Kubernetes deployment options. | Feldera offers Docker for local development, testing, and prototyping, a free online sandbox, and an enterprise offering for production. |
| Purpose | Apache Spark is a unified engine for large-scale data analytics. | Feldera is an incremental view maintenance engine that keeps SQL views in sync with changing data and works alongside a lakehouse or warehouse. |
| Security | Security features such as authentication are not enabled by default, and the documentation says deployments are not secure by default. | The Trust Center lists SOC 2 Type 1 and Type 2 compliance and offers access to security documentation, including a penetration test report and SOC 2 report. |
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.
Feldera
Feldera is an incremental view maintenance engine that keeps SQL views current as input data changes, for use alongside a lakehouse or warehouse. Instead of rebuilding a full dataset after each change, it updates views in proportion to the change. It supports SQL window functions and recursive queries. Documented inputs include Kafka, Google Pub/Sub, NATS, PostgreSQL, AWS S3, Delta Lake, and Apache Iceberg; outputs include Kafka, Delta Lake, PostgreSQL, Redis, DynamoDB, Snowflake, and Iceberg, with several output connectors marked experimental. The free open-source edition runs as a single node and container, supports all connectors and datasets larger than memory, and includes community support through Slack. Docker is available for local development, testing, and prototyping, alongside a free online sandbox. Enterprise runs on a customer-provided cloud or Kubernetes cluster and adds multi-node deployments, fault tolerance, resource isolation, and dedicated support. Its documentation says data stays on the customer's premises. Enterprise pricing is custom, and pipeline scale-out is listed as coming soon.