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Comparison · Analytics
Countly vs Apache Storm
A side-by-side editorial comparison of Countly and Apache Storm — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:security
Countly vs Apache Storm: at a glance
What is Countly?
Countly's two LTS lines now get the same security fixes within a week of each other.
Countly ships security patches on two LTS lines, 25.03 and 24.05. In late October 25.03.56 moved the Docker images to Node.js 24.22.1 for a Brotli CVE and brought Python 3.12.15 to the A/B testing stack; 25.03.58 tightened tokens: app-restricted tokens must state their permissions, password changes revoke a member's tokens, and single-use tokens hold under concurrent requests. 24.05.55 then brought those same fixes to the older line, including the isolated-vm sandbox for custom hook code that 25.03 adopted in August.
What is Apache Storm?
Storm 3.1 adds an Iceberg sink and closes a long list of security gaps in Nimbus and the UI.
Storm runs a 3.x line, started in July with 3.0.0's removal of all Clojure and a Java 21 baseline, alongside 2.8.x maintenance. 3.1.0 on September 12 adds a storm-iceberg module with an Apache Iceberg sink bolt and a setting to control JSONP wrapping, and spends most of its notes on hardening: log listings filtered by user permission, jar locations restricted to the Nimbus inbox, blobstore names confined to topology directories, TLS peer verification for worker connections and required Kryo class registration.
Countly vs Apache Storm: editorial side-by-side
Countly
5.0ANALYTICS
Countly's two LTS lines now get the same security fixes within a week of each other.
◆ Current state
Countly ships security patches on two LTS lines, 25.03 and 24.05. In late October 25.03.56 moved the Docker images to Node.js 24.22.1 for a Brotli CVE and brought Python 3.12.15 to the A/B testing stack; 25.03.58 tightened tokens: app-restricted tokens must state their permissions, password changes revoke a member's tokens, and single-use tokens hold under concurrent requests. 24.05.55 then brought those same fixes to the older line, including the isolated-vm sandbox for custom hook code that 25.03 adopted in August.
◆ Where it's heading
The work is about access control and supply chain, not new analytics features. Tokens, sessions and login counting are being tightened release by release, and the 24.05 line is being pulled up to the 25.03 runtime (Node.js 22 for custom code, Python 3.12 with CmdStanPy for A/B testing) instead of being left on older stacks. Feature work shows up only in small items such as explicitly named databases and a licence payment-overdue banner.
◆ Prediction
Expect more paired patches as token and session hardening continues on both lines. The entries don't say how long 24.05 will keep receiving backports.
Apache Storm
0.0ANALYTICS
Storm 3.1 adds an Iceberg sink and closes a long list of security gaps in Nimbus and the UI.
◆ Current state
Storm runs a 3.x line, started in July with 3.0.0's removal of all Clojure and a Java 21 baseline, alongside 2.8.x maintenance. 3.1.0 on September 12 adds a storm-iceberg module with an Apache Iceberg sink bolt and a setting to control JSONP wrapping, and spends most of its notes on hardening: log listings filtered by user permission, jar locations restricted to the Nimbus inbox, blobstore names confined to topology directories, TLS peer verification for worker connections and required Kryo class registration.
◆ Where it's heading
After the 2.8.6 and 2.8.7 CVE releases, the 3.x line is closing access-control gaps across Nimbus, the logviewer and worker transport. The Iceberg sink adds a direct path into lakehouse storage.
◆ Prediction
Expect 3.1.x follow-ups, possibly with security advisories for the hardened paths, and continued 2.8.x maintenance; whether more lakehouse connectors follow is unclear.
Alternatives to Countly 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 Countly or Apache Storm.
Apache Iceberg
Iceberg 1.12 drops Spark 3.4 and starts laying groundwork for the v4 table spec.
ManageEngine Log360
Log360's September build fixes the migration to the unified console.
Deepnote
Deepnote's agent now runs from first prompt to finished notebook without handoffs.
Apache HertzBeat
HertzBeat's 1.9.0 is on its second release candidate, and the feed still skips 1.8.0.
OpenPanel
OpenPanel moves from 3.18 to 3.20 in two days, still without a word of release notes.
See all Countly alternatives → · See all Apache Storm alternatives →
Recent activity from Countly and Apache Storm
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3d agoCountlyCountly Version 24.05.55
- 6d agoCountlyCountly Version 25.03.58
- 7d agoCountlyCountly Version 25.03.57-LTS
- 10d agoCountlyCountly Version 25.03.56-LTS
- 21d agoCountlyCountly Version 25.03.55
- 1mo agoCountlyCountly Version 24.05.54
- 1mo agoApache StormStorm 3.1.0 adds an Iceberg sink and security hardening
- 3mo agoApache StormStorm 3.0 drops Clojure entirely and moves to Java 21 ⚡
- 3mo agoApache Storm2.8.9 is a dependency sweep with one Flux viewer guard
- 3mo agoApache Storm2.8.8 backports a Kafka topology-lag fix
- 6mo agoApache StormTwo TLS CVEs fixed: JVM-wide downgrade and auth bypass
- 6mo agoApache StormDeserialization RCE and stored XSS in the UI are fixed
Frequently asked questions
What is the difference between Countly and Apache Storm?
Both compete on the same themes — security — within Analytics. Countly is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is Countly better than Apache Storm?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Countly is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to Countly?
Top Countly alternatives in Analytics are ranked by recent ship velocity. Browse the "Countly alternatives" section above for the current picks, or visit /alternatives/countly 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.