Apache Storm vs Google Cloud Dataflow
No leader: the top candidate Apache Storm has only 0.28 confidence (low), below the 0.35 needed to declare a winner. The attribute-by-attribute breakdown below, with a source and date on every value, is the honest way to compare them.
Capabilities
Feature-by-feature on the axes that matter for streaming analytics. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
Apache Storm
An open-source system designed to handle continuous streams of information quickly and reliably, without stopping, with built-in protections against data loss.
Google Cloud Dataflow
A unified data processing platform that supports real-time ETL, stream analytics, machine learning inference, and complex transformations using Apache Beam, running on Google Cloud infrastructure with automatic scaling.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Google Cloud Dataflow
Pricing not documented yet.
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
Apache Storm
- Hadoop
- Kafka
Google Cloud Dataflow
- Apache Beam
- Splunk
- Google Cloud Notebooks
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.