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Deepnote vs Apache Storm

A side-by-side editorial comparison of Deepnote and Apache Storm — release velocity, themes, recent moves, and the top alternatives to consider.

Deepnote vs Apache Storm: at a glance

FeatureDeepnoteApache Storm
SectorAnalyticsAnalytics
Velocity score6.36.3
Sparks · 30d01
Top themesdata notebooks, agentic ai, mcp, reproducibilitystream-processing, modernization, security, scheduler
Last editorial update1mo ago2d ago
WebsiteVisit →

What is Deepnote?

Deepnote reshapes the data notebook into agent-operable infrastructure.

Deepnote, a collaborative data-science notebook, is steadily making itself agent-native: MCP tools now let AI agents create and wire integrations end-to-end, and OpenAI's Codex connects natively to a Deepnote workspace's notebooks, schedules, and data. Underneath, it keeps shipping solid workflow features — run snapshots, Git and GitLab sync, Polars, PDF export.

Read the full Deepnote trajectory →

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.

Read the full Apache Storm trajectory →

Deepnote vs Apache Storm: editorial side-by-side

D
Deepnote
ANALYTICS
6.3

Deepnote reshapes the data notebook into agent-operable infrastructure.

◆ Current state

Deepnote, a collaborative data-science notebook, is steadily making itself agent-native: MCP tools now let AI agents create and wire integrations end-to-end, and OpenAI's Codex connects natively to a Deepnote workspace's notebooks, schedules, and data. Underneath, it keeps shipping solid workflow features — run snapshots, Git and GitLab sync, Polars, PDF export.

◆ Where it's heading

Two tracks are converging: reproducibility and engineering rigor (immutable run snapshots, Git sync, notebook interoperability) and agent-operability (MCP tools, Codex context). Deepnote is positioning the workspace as the trusted context layer that AI agents act through, not just a place humans write notebooks.

◆ Prediction

Expect more MCP tooling that lets agents operate Deepnote projects autonomously, plus deeper native hooks for external coding agents — the workspace-as-agent-context bet will likely expand beyond Codex.

A
Apache Storm
ANALYTICS
6.3

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 Deepnote 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 Deepnote or Apache Storm.

See all Deepnote alternatives → · See all Apache Storm alternatives →

Recent activity from Deepnote and Apache Storm

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 20d agoApache StormStorm 3.0 drops Clojure entirely and moves to Java 21
  2. 20d agoApache Storm2.8.9 is a dependency sweep with one Flux viewer guard
  3. 20d agoApache Storm2.8.8 backports a Kafka topology-lag fix
  4. 1mo agoDeepnoteNew MCP tools for integrations
  5. 2mo agoDeepnoteYour workspace as the context for every exploration
  6. 3mo agoDeepnoteRun snapshots, Git sync, & AI usage visibility
  7. 3mo agoDeepnoteRun snapshots, Git sync, Polars support, PDF export, & a cleaner notebook
  8. 3mo agoDeepnoteRun snapshots, Git sync, Polars support, PDF export, & a cleaner notebook
  9. 3mo agoApache StormTwo TLS CVEs fixed: JVM-wide downgrade and auth bypass
  10. 3mo agoApache StormDeserialization RCE and stored XSS in the UI are fixed
  11. 4mo agoDeepnotePolars support, PDF export & a cleaner notebook
  12. 4mo agoApache Storm2.8.5 is dependency upgrades plus small logging fixes

Frequently asked questions

What is the difference between Deepnote and Apache Storm?

They serve adjacent needs but don't currently overlap on shipped themes. Deepnote 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 Deepnote better than Apache Storm?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Deepnote 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 Deepnote?

Top Deepnote alternatives in Analytics are ranked by recent ship velocity. Browse the "Deepnote alternatives" section above for the current picks, or visit /alternatives/deepnote 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.