Apache Heron vs Feldera
Apache Heron
heron.apache.orgFeldera
feldera.comSide by side
| Figure | Apache Heron | Feldera |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 2 |
| Spec score · Streaming Analytics Software | 7.5 (#16) | 7.8 (#12) |
| Spec score · Stream Processing Software | 7.5 (#18) | 7.8 (#14) |
| Community support | The README lists user and development mailing lists and a Heron Slack workspace. | The open source edition provides community support through Slack. |
| Purpose | Heron is a real-time, distributed, fault-tolerant stream processing engine. | Feldera is an incremental view maintenance engine that keeps SQL views in sync with changing data and works alongside a lakehouse or warehouse. |
| Security | The GitHub repository page links to a security policy. | 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 Heron
Apache Heron has no write-up on Specifiction yet; its figures are above.
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.