Apache Storm vs Feldera
Apache Storm
storm.apache.orgFeldera
feldera.comSide by side
| Figure | Apache Storm | Feldera |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | 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 | 8.0 (#8) | 7.8 (#12) |
| Spec score · Stream Processing Software | 8.1 (#9) | 7.8 (#14) |
| Deployment | Storm provides local mode for in-process development and remote mode for submitting topologies to a cluster. | Feldera offers Docker for local development, testing, and prototyping, a free online sandbox, and an enterprise offering for production. |
| Performance | The project says a benchmark processed over one million tuples per second per node. | The product page says Feldera can process complex pipelines with millions of changes per second, including on a laptop. |
| Purpose | Apache Storm is a distributed realtime computation system for reliably processing unbounded data streams. | Feldera is an incremental view maintenance engine that keeps SQL views in sync with changing data and works alongside a lakehouse or warehouse. |
| Security | Storm supports pluggable Kerberos/SASL authentication and SimpleACLAuthorizer authorization, both disabled 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. |
| Use cases | Storm supports realtime analytics, online machine learning, continuous computation, distributed RPC, and ETL. | Feldera presents real-time medallion architectures, fraud detection feature engineering, and fine-grained authorization as use cases. |
Plans
In their own words
Apache Storm
Apache Storm is a distributed system for computing over unbounded data streams in real time. It uses spouts, bolts, and topologies to assemble multi-stage computations, supporting realtime analytics, online machine learning, continuous computation, distributed RPC, and ETL. The project describes Storm as scalable and fault-tolerant, with guaranteed data processing, and reports a benchmark above one million tuples per second per node. Integrations include Apache Kafka, HDFS, JDBC databases, JMS, and Redis. Developers can work in local mode in-process or submit topologies to a remote cluster. Storm supports stateful processing and lists JavaScript, Python, Ruby, and C# among supported languages. It is free under Apache License, Version 2.0; source and binary distributions are available, along with Maven Central and an official Docker image. The current release is 3.1.0. Security options include Kerberos/SASL authentication, SimpleACLAuthorizer authorization, and TLS for Thrift RPC and worker messaging; authentication and authorization options are disabled by default.
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.