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RecoveryManager Plus keeps widening its backup coverage across the Microsoft identity estate.
A side-by-side editorial comparison of silx and Apache Storm — release velocity, themes, recent moves, and the top alternatives to consider.
silx settles into maintenance a release after its PySide6 migration
silx is in the quiet phase after a generational release. 3.1.1 is a single fix to FitWidget loading a fit function from file. The release before it, 3.1.0, was the first real feature work since the migration - asinh axis scaling, twilight colormaps, and dark-theme icons - and 3.0.1 was similarly small. The 3.0.0 cut that reset the Qt binding and Python floor still defines what the line is doing.
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.
silx is in the quiet phase after a generational release. 3.1.1 is a single fix to FitWidget loading a fit function from file. The release before it, 3.1.0, was the first real feature work since the migration - asinh axis scaling, twilight colormaps, and dark-theme icons - and 3.0.1 was similarly small. The 3.0.0 cut that reset the Qt binding and Python floor still defines what the line is doing.
The cadence has slowed markedly since April, and the content has shifted from structural change to plotting and colormap refinement. That is the expected shape after a binding migration: downstream beamline code needs a stable target, so the project trades feature velocity for a quiet surface. The gap between 3.0.1 in May and 3.1.0 in August is the clearest signal of the deliberate slowdown.
Expect further point releases servicing the plotting and fitting widgets rather than another structural change, with feature work continuing to arrive in the 3.1.x minors rather than patches.
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.
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.
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.
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 silx or Apache Storm.
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See all silx alternatives → · See all Apache Storm alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Apache Storm is currently shipping more aggressively (velocity 6.3 vs 5.0), with 1 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Apache Storm is currently shipping more aggressively (velocity 6.3 vs 5.0), with 1 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.
Top silx alternatives in Analytics are ranked by recent ship velocity. Browse the "silx alternatives" section above for the current picks, or visit /alternatives/silx for the full list with editorial commentary on each.
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.