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Comparison · Analytics
Apache TsFile vs Apache Storm
A side-by-side editorial comparison of Apache TsFile and Apache Storm — release velocity, themes, recent moves, and the top alternatives to consider.
Apache TsFile vs Apache Storm: at a glance
What is Apache TsFile?
TsFile is quietly rebuilding itself as an Arrow-speaking interchange format
Apache TsFile is the columnar time-series file format underlying IoTDB, maintained as three parallel implementations in Java, C++ and Python. Recent releases have concentrated on the C++ and Python ends: SIMD paths and parallel reads in 2.4.0, an Arrow-compatible result path from C++ through to Python DataFrames in 2.3.0, and conversion scripts from CSV, Parquet and Arrow into TsFile in 2.3.1. The Java side gets steadier, smaller work — serialized-size calculation, schema modification during writes, encryption configuration.
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.
Apache TsFile vs Apache Storm: editorial side-by-side
Apache TsFile
2.5ANALYTICS
TsFile is quietly rebuilding itself as an Arrow-speaking interchange format
◆ Current state
Apache TsFile is the columnar time-series file format underlying IoTDB, maintained as three parallel implementations in Java, C++ and Python. Recent releases have concentrated on the C++ and Python ends: SIMD paths and parallel reads in 2.4.0, an Arrow-compatible result path from C++ through to Python DataFrames in 2.3.0, and conversion scripts from CSV, Parquet and Arrow into TsFile in 2.3.1. The Java side gets steadier, smaller work — serialized-size calculation, schema modification during writes, encryption configuration.
◆ Where it's heading
The centre of gravity has moved from format features to ecosystem reach. Arrow-backed DataFrames and format converters are not about storing time series better; they are about making TsFile readable by the Python analytics stack without a translation layer, which is the gap that keeps a specialized format confined to its own database. The C++ performance work in 2.4.0 serves the same end, since the Python bindings sit on top of it. Version numbering runs on two lines at once, with 1.1.x backports still shipping alongside the 2.x series.
◆ Prediction
Given the direction of the Arrow work, the Python interface is the most likely target for further capability rather than the Java one. The notes do not indicate when the 1.1 maintenance line ends.
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 Apache TsFile 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 Apache TsFile or Apache Storm.
OpenDataDiscovery
Four ODD Platform releases in two weeks, and not one of them changes the product
Apache Baremaps
Baremaps got geoparquet and hillshading, then went quiet for eighteen months in incubation
Deequ
Deequ ships GitHub tags whose release notes are one commit message long
Marquez
Marquez spent 2024 turning a lineage store into a UI, then stopped releasing
Amundsen
Amundsen's last release was a config flag, and the feed has been silent for two years
See all Apache TsFile alternatives → · See all Apache Storm alternatives →
Recent activity from Apache TsFile and Apache Storm
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 19d agoApache TsFileSIMD and parallel read paths in Apache TsFile 2.4.0
- 19d agoApache StormStorm 3.0 drops Clojure entirely and moves to Java 21 ⚡
- 19d agoApache Storm2.8.9 is a dependency sweep with one Flux viewer guard
- 19d agoApache Storm2.8.8 backports a Kafka topology-lag fix
- 2mo agoApache TsFileCSV, Parquet and Arrow conversion scripts for TsFile 2.3.1
- 3mo agoApache TsFileArrow-backed DataFrames and paginated reads in TsFile 2.3.0
- 3mo agoApache StormTwo TLS CVEs fixed: JVM-wide downgrade and auth bypass
- 3mo agoApache StormDeserialization RCE and stored XSS in the UI are fixed
- 3mo agoApache TsFileWrite-time schema changes and read/write encryption in TsFile 2.2.1
- 4mo agoApache Storm2.8.5 is dependency upgrades plus small logging fixes
- 7mo agoApache TsFilePython text types and C++ tag filtering in TsFile 2.2.0
- 7mo agoApache TsFileBackport maintenance on the TsFile 1.1 line
Frequently asked questions
What is the difference between Apache TsFile and Apache Storm?
They serve adjacent needs but don't currently overlap on shipped themes. Apache Storm is currently shipping more aggressively (velocity 6.3 vs 2.5), 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.
Is Apache TsFile better than Apache Storm?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Apache Storm is currently shipping more aggressively (velocity 6.3 vs 2.5), 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.
What are the best alternatives to Apache TsFile?
Top Apache TsFile alternatives in Analytics are ranked by recent ship velocity. Browse the "Apache TsFile alternatives" section above for the current picks, or visit /alternatives/apache-tsfile 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.