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Comparison · Analytics
stacks vs TimescaleDB
A side-by-side editorial comparison of stacks and TimescaleDB — release velocity, themes, recent moves, and the top alternatives to consider.
stacks vs TimescaleDB: at a glance
What is stacks?
Model stacking in tidymodels, quietly migrating off foreach and onto future
stacks builds ensembles from tidymodels tuning results, and its release history is dominated by one long project: replacing foreach-based parallelism with the future framework. That transition completed in 1.1.0, where foreach backends began being ignored with a warning and the minimum R version rose to 4.1. Releases are infrequent and small, with the most recent being a CRAN re-submission rather than a change.
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.
stacks vs TimescaleDB: editorial side-by-side
stacks
0.0ANALYTICS
Model stacking in tidymodels, quietly migrating off foreach and onto future
◆ Current state
stacks builds ensembles from tidymodels tuning results, and its release history is dominated by one long project: replacing foreach-based parallelism with the future framework. That transition completed in 1.1.0, where foreach backends began being ignored with a warning and the minimum R version rose to 4.1. Releases are infrequent and small, with the most recent being a CRAN re-submission rather than a change.
◆ Where it's heading
The package is mature and its remaining work is compatibility rather than capability — tracking the parallelism story across tidymodels, keeping object sizes sane after butchering and reloading, and staying aligned with recipes deprecations. The augment() method added for vetiver compatibility shows the same instinct: fit into the surrounding ecosystem rather than grow independently of it. Nothing in the visible history suggests new ensembling methods are being pursued.
◆ Prediction
With the future migration finished, the next release is most likely maintenance keeping pace with tune and recipes rather than anything users would notice.
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 stacks 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 stacks or TimescaleDB.
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.
Usermaven
Usermaven closed the loop: data comes in from anywhere, and now it goes back out.
See all stacks alternatives → · See all TimescaleDB alternatives →
Recent activity from stacks 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
- 1y agostacksstacks 1.1.1 re-released to clear a CRAN check note
- 1y agostacksstacks 1.1.0 completes the move to future-based parallelism
- 2y agostacksstacks 1.0.5 fixes butchered stack size inflation
- 2y agostacksstacks 1.0.4 introduces future-based parallel processing
- 2y agostacksstacks 1.0.3 clears recipes deprecations and a type-check bug
- 3y agostacksstacks 1.0.2 adds an augment() method for vetiver compatibility
Frequently asked questions
What is the difference between stacks 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 stacks 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 stacks?
Top stacks alternatives in Analytics are ranked by recent ship velocity. Browse the "stacks alternatives" section above for the current picks, or visit /alternatives/stacks 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.