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Comparison · Analytics
Apache Storm vs Dagster
A side-by-side editorial comparison of Apache Storm and Dagster — release velocity, themes, recent moves, and the top alternatives to consider.
Apache Storm vs Dagster: at a glance
What is Apache Storm?
Storm 3.0 finishes removing the Clojure it was built in, and moves to a Java 21 baseline.
Storm is running two lines: a 2.8.x maintenance branch that is mostly Dependabot traffic punctuated by real security releases, and the new 3.0.0 line cut on 22 July. 3.0.0 removes all remaining Clojure from the codebase, raises the baseline to Java 21 (with master already on 25), and ships throughput work — zstd compression for thrift cluster state, tuple compression between workers, and decoupling of the control plane from the data plane on receive queues. The 2.8.6 and 2.8.7 releases earlier in the window carried four CVEs, including a deserialization RCE reachable by any user with topology submission rights.
What is Dagster?
Dagster's declarative automation grows past assets while the UI is rebuilt for scale.
Dagster ships weekly 1.13.x point releases, each pairing a short list of new capability with a longer list of fixes. The through-line is Declarative Automation, the asset-condition system that separates Dagster from schedule-driven orchestrators, which has now reached jobs. Running alongside it is a sustained effort to keep the UI responsive in workspaces whose asset graphs outgrew the original interface.
Apache Storm vs Dagster: editorial side-by-side
Apache Storm
6.3ANALYTICS
Storm 3.0 finishes removing the Clojure it was built in, and moves to a Java 21 baseline.
◆ Current state
Storm is running two lines: a 2.8.x maintenance branch that is mostly Dependabot traffic punctuated by real security releases, and the new 3.0.0 line cut on 22 July. 3.0.0 removes all remaining Clojure from the codebase, raises the baseline to Java 21 (with master already on 25), and ships throughput work — zstd compression for thrift cluster state, tuple compression between workers, and decoupling of the control plane from the data plane on receive queues. The 2.8.6 and 2.8.7 releases earlier in the window carried four CVEs, including a deserialization RCE reachable by any user with topology submission rights.
◆ Where it's heading
The project is converting itself from a legacy JVM codebase into an ordinary modern Java one, and the 3.0 work shows where that energy goes next: scheduling and queueing. Recent PRs add AIMD dynamic batch sizing to JCQueue, jitter metrics and a jitter-aware stream grouping, round-robin rebalance onto returning supervisors, and several fixes for stale or orphaned worker heartbeats. Alongside that, the distribution is being slimmed — optional Hadoop and Kafka dependencies were unbundled and shared jars de-duplicated. The 2.x branch is being kept alive for security and dependency currency, not for features.
◆ Prediction
Expect 3.0.x point releases to concentrate on the scheduler and worker-lifecycle fixes that 3.0.0 opened up, and expect the 2.8.x line to keep receiving CVE backports while feature work stays on 3.x. The Java 25 baseline already on master suggests the next minor will move the floor again.
Dagster
6.3ANALYTICS
Dagster's declarative automation grows past assets while the UI is rebuilt for scale.
◆ Current state
Dagster ships weekly 1.13.x point releases, each pairing a short list of new capability with a longer list of fixes. The through-line is Declarative Automation, the asset-condition system that separates Dagster from schedule-driven orchestrators, which has now reached jobs. Running alongside it is a sustained effort to keep the UI responsive in workspaces whose asset graphs outgrew the original interface.
◆ Where it's heading
Automation is escaping the asset boundary. Conditions can now launch jobs, which brings the declarative model to the parts of a deployment that never fit the asset abstraction and where users fell back to schedules. Several consecutive releases also spend their effort on virtualized lists, bounded previews and scoped search — the signature of a product whose largest customers hit the UI's limits first. Preview flags on both the job automation and the Snowflake component indicate neither is finished.
◆ Prediction
Expect Declarative Automation for jobs to move from preview to general availability within the 1.13.x line, and more first-party Components covering the remaining warehouse and dbt paths.
Alternatives to Apache Storm and Dagster
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either Apache Storm or Dagster.
Cortex
Cortex is betting on Parquet block storage and graduating years of experimental features.
NetObserv
NetObserv is layering TLS visibility and health alerting on top of its eBPF flow pipeline.
Apache StreamPark
Five release candidates in two years, none of them stable, and none since October 2025.
Apache HertzBeat
A monitoring project whose public release feed skips the release that mattered.
Axiom
Axiom is rebuilding observability so an AI agent, not a human, can be the first user.
See all Apache Storm alternatives → · See all Dagster alternatives →
Recent activity from Apache Storm and Dagster
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoDagsterRetry-pending failures now warn instead of degrading
- 9d agoDagsterDeclarative Automation can now launch jobs (preview) ⚡
- 16d agoDagsterSnowflake dbt component preview and MCP server docs
- 17d agoApache StormStorm 3.0 drops Clojure entirely and moves to Java 21 ⚡
- 17d agoApache Storm2.8.9 is a dependency sweep with one Flux viewer guard
- 17d agoApache Storm2.8.8 backports a Kafka topology-lag fix
- 23d agoDagsterServerless I/O manager 401 and 400 errors fixed
- 1mo agoDagsterInstall-time protobuf version conflict fixed
- 1mo agoDagsterRuns feed bounded previews and an automation tick fix
- 3mo agoApache StormTwo TLS CVEs fixed: JVM-wide downgrade and auth bypass
- 3mo agoApache StormDeserialization RCE and stored XSS in the UI are fixed
- 4mo agoApache Storm2.8.5 is dependency upgrades plus small logging fixes
Frequently asked questions
What is the difference between Apache Storm and Dagster?
They serve adjacent needs but don't currently overlap on shipped themes. Apache Storm and Dagster are shipping at a similar cadence (velocity 6.3 vs 6.3, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is Apache Storm better than Dagster?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Apache Storm and Dagster are shipping at a similar cadence (velocity 6.3 vs 6.3, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to Apache Storm?
Top Apache Storm alternatives in Analytics are ranked by recent ship velocity. Browse the "Apache Storm alternatives" section above for the current picks, or visit /alternatives/storm for the full list with editorial commentary on each.
What are the best alternatives to Dagster?
Top Dagster alternatives in Analytics are ranked by recent ship velocity. Browse the "Dagster alternatives" section above for the current picks, or visit /alternatives/dagster for the full list with editorial commentary on each.