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Comparison · Analytics
Plotly vs Apache Storm
A side-by-side editorial comparison of Plotly and Apache Storm — release velocity, themes, recent moves, and the top alternatives to consider.
Plotly vs Apache Storm: at a glance
What is Plotly?
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
Plotly ships on two tracks. Plotly Studio, the desktop AI app-builder, releases every one to two weeks and has spent v0.0.80 through v0.0.86 on credential handling, reasoning transparency, personalization and now the reliability of the agent session engine itself. Plotly Cloud is the louder track: since late May it has added viewer-seat pricing, domain verification, per-app compute modes with credit-metered billing, and customer-owned domains with managed TLS.
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.
Plotly vs Apache Storm: editorial side-by-side
Plotly
6.3ANALYTICS
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
◆ Current state
Plotly ships on two tracks. Plotly Studio, the desktop AI app-builder, releases every one to two weeks and has spent v0.0.80 through v0.0.86 on credential handling, reasoning transparency, personalization and now the reliability of the agent session engine itself. Plotly Cloud is the louder track: since late May it has added viewer-seat pricing, domain verification, per-app compute modes with credit-metered billing, and customer-owned domains with managed TLS.
◆ Where it's heading
The Cloud releases are assembling the standard pieces of a hosting business in order — identity first (domain verification, explicitly framed as the step before SSO), then billing (viewer seats, then metered compute credits), and now production-grade serving (custom domains, automatic certificate renewal). Studio is being hardened as the authoring front end that feeds it: Universal Deployment pushed beyond Dash apps, credentials saved once and reused, a Winget channel to widen Windows installs, and in v0.0.86 a rebuilt session engine plus automatic retries so agent runs survive expired tokens. The two tracks converge on one funnel — author in Studio, deploy to Cloud, pay by compute consumed.
◆ Prediction
The Domain Verification entry names SSO as the next step and places it in the Enterprise tier, so single sign-on is the most likely Cloud release next. Studio should hold its one-to-two-week cadence, with the newly added app thumbnails pointing toward more work on browsing and organizing generated apps.
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.
Alternatives to Plotly and Apache Storm
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 Plotly or Apache Storm.
silx
silx settles into maintenance a release after its PySide6 migration
aniread
aniread stops asking you to know which tracker wrote the file
Rho
Rho's release machinery finally produced a stable build — and it shipped no new product.
Usermaven
Usermaven closed the loop: data comes in from anywhere, and now it goes back out.
OpenCTI
OpenCTI spends a release unblocking queues and hardening upserts
See all Plotly alternatives → · See all Apache Storm alternatives →
Recent activity from Plotly and Apache Storm
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 14d agoPlotlyCustom Domains in Plotly Cloud ⚡
- 24d agoPlotlyPlotly Studio v0.0.85: Breadcrumbs & minor bug fixes
- 27d agoApache StormStorm 3.0 drops Clojure entirely and moves to Java 21 ⚡
- 27d agoApache Storm2.8.9 is a dependency sweep with one Flux viewer guard
- 27d agoApache Storm2.8.8 backports a Kafka topology-lag fix
- 1mo agoPlotlyPlotly Studio v0.0.84: Faster AI, Saved Credentials, and Winget Support
- 1mo agoPlotlyCompute Modes and App Sizing in Plotly Cloud ⚡
- 1mo agoPlotlyPlotly Studio 0.0.83: Dash Update and macOS Fixes
- 2mo agoPlotlyPlotly Studio v0.0.82: Override for credential redaction, stability fixes
- 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 Plotly and Apache Storm?
They serve adjacent needs but don't currently overlap on shipped themes. Plotly and Apache Storm 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 Plotly better than Apache Storm?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Plotly and Apache Storm 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 Plotly?
Top Plotly alternatives in Analytics are ranked by recent ship velocity. Browse the "Plotly alternatives" section above for the current picks, or visit /alternatives/plotly for the full list with editorial commentary on each.
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.