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Comparison · Analytics
statsmodels vs TimescaleDB
A side-by-side editorial comparison of statsmodels and TimescaleDB — release velocity, themes, recent moves, and the top alternatives to consider.
statsmodels vs TimescaleDB: at a glance
What is statsmodels?
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
Every release in this window is a compatibility release. 0.14.2 and 0.14.3 absorbed NumPy 2, 0.14.5 fixed an import failure caused by SciPy 1.16, and 0.14.6 did the same for pandas 3.0. The only additive change across two years is Pyodide support in 0.14.4, described in its own notes as one feature and no fixes. A 0.15.0.dev0 tag exists from 2023 and has not been followed by a 0.15 release.
What is TimescaleDB?
TimescaleDB is paying down correctness debt in its columnstore query paths.
The 2.29 line is in patch mode after 2.29.0 landed chunk exclusion for DML in late July. 2.29.1 carried three security advisories alongside compression fixes, and 2.29.2 is bug fixes only - most of them wrong-results bugs in the columnar execution paths rather than crashes. Every release note in this window recommends upgrading at the next opportunity.
statsmodels vs TimescaleDB: editorial side-by-side
statsmodels
0.0ANALYTICS
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
◆ Current state
Every release in this window is a compatibility release. 0.14.2 and 0.14.3 absorbed NumPy 2, 0.14.5 fixed an import failure caused by SciPy 1.16, and 0.14.6 did the same for pandas 3.0. The only additive change across two years is Pyodide support in 0.14.4, described in its own notes as one feature and no fixes. A 0.15.0.dev0 tag exists from 2023 and has not been followed by a 0.15 release.
◆ Where it's heading
The library is being kept alive rather than developed: each release answers a break introduced upstream, and the interval between them is set by the NumPy, SciPy and pandas release calendars rather than by anything statsmodels is building. Two consecutive releases whose stated purpose was restoring the ability to import the package is the sharpest available signal about maintainer bandwidth. The 0.15 line remains a dev tag with no visible progress toward a release.
◆ Prediction
The next release is most likely another compatibility patch triggered by a NumPy, SciPy or pandas major, and nothing in these entries indicates 0.15 is close.
TimescaleDB
5.0ANALYTICS
TimescaleDB is paying down correctness debt in its columnstore query paths.
◆ Current state
The 2.29 line is in patch mode after 2.29.0 landed chunk exclusion for DML in late July. 2.29.1 carried three security advisories alongside compression fixes, and 2.29.2 is bug fixes only - most of them wrong-results bugs in the columnar execution paths rather than crashes. Every release note in this window recommends upgrading at the next opportunity.
◆ Where it's heading
The feature work of 2.27 and 2.28 - vectorized filter evaluation, first/last derived straight from columnstore batch metadata, sparse indexes, SkipScan on compressed data - has been followed by a steady stream of fixes to those same code paths. 2.29.2 alone repairs SkipScan dropping uncompressed rows, sparse-index pushdown returning wrong results for IS NULL, and gapfill over window aggregates. That is the normal cost of pushing query optimizations into a compressed columnar store, and the project is working through it release by release rather than pausing.
◆ Prediction
With three consecutive patch releases on the 2.29 line and no new highlighted features since 2.29.0, the next minor is likely to resume the columnstore performance work - though the density of wrong-results fixes suggests more patches first.
Alternatives to statsmodels and TimescaleDB
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 statsmodels or TimescaleDB.
Omni
Omni ships weekly, and almost every week the headline item is an AI feature.
silx
silx settles into maintenance a release after its PySide6 migration
Plotly
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
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.
See all statsmodels alternatives → · See all TimescaleDB alternatives →
Recent activity from statsmodels and TimescaleDB
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoTimescaleDB2.29.2: SkipScan and sparse-index correctness fixes
- 15d agoTimescaleDB2.29.1: security fixes plus compression bugfixes
- 19d agoTimescaleDB2.29.0: chunk exclusion speeds up UPDATE and DELETE
- 1mo agoTimescaleDB2.28.3: columnar pipeline correctness fixes
- 1mo agoTimescaleDB2.28.2: upgrade-path fixes for 2.28.1
- 1mo agoTimescaleDB2.28.1: compressed-table crash and constraint fixes
- 8mo agostatsmodels0.14.6: restores importing under pandas 3.0
- 1y agostatsmodels0.14.5: restores importing under SciPy 1.16
- 1y agostatsmodels0.14.4: Pyodide support
- 1y agostatsmodels0.14.3: NumPy 2 environments and corrected macOS builds
- 2y agostatsmodels0.14.2: full NumPy 2 compatibility
- 2y agostatsmodelsstatsmodels 0.14.1 is a bug-fix release with no API changes
Frequently asked questions
What is the difference between statsmodels and TimescaleDB?
They serve adjacent needs but don't currently overlap on shipped themes. TimescaleDB 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 statsmodels better than TimescaleDB?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. TimescaleDB 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 statsmodels?
Top statsmodels alternatives in Analytics are ranked by recent ship velocity. Browse the "statsmodels alternatives" section above for the current picks, or visit /alternatives/statsmodels for the full list with editorial commentary on each.
What are the best alternatives to TimescaleDB?
Top TimescaleDB alternatives in Analytics are ranked by recent ship velocity. Browse the "TimescaleDB alternatives" section above for the current picks, or visit /alternatives/timescaledb for the full list with editorial commentary on each.