Omni
Omni ships weekly, and almost every week the headline item is an AI feature.
A side-by-side editorial comparison of feasts and TimescaleDB — release velocity, themes, recent moves, and the top alternatives to consider.
feasts is splitting itself in two, moving every plot into ggtime
feasts provides feature extraction and statistics for tsibble time series. The last two releases are dominated by one decision: all of its gg_*() plotting functions are being moved out into a separate ggtime package. 0.4.2 announced the deprecation and 0.5.0 makes ggtime a dependency with soft-deprecation messages on every re-export.
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.
feasts provides feature extraction and statistics for tsibble time series. The last two releases are dominated by one decision: all of its gg_*() plotting functions are being moved out into a separate ggtime package. 0.4.2 announced the deprecation and 0.5.0 makes ggtime a dependency with soft-deprecation messages on every re-export.
The package is narrowing to its stated purpose — features and statistics — and shedding graphics entirely over a deliberately slow two-year window. Everything else in the recent history is ggplot2 compatibility work and narrow seasonal-plot bug fixes, which is consistent with a maintainer trimming surface area rather than growing it.
The next releases should be compatibility upkeep while the ggtime deprecation runs its course; the re-exports stay until the announced window closes.
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.
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.
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.
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 feasts or TimescaleDB.
Omni ships weekly, and almost every week the headline item is an AI feature.
silx settles into maintenance a release after its PySide6 migration
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
aniread stops asking you to know which tracker wrote the file
Rho's release machinery finally produced a stable build — and it shipped no new product.
Usermaven closed the loop: data comes in from anywhere, and now it goes back out.
See all feasts alternatives → · See all TimescaleDB alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — time-series — within Analytics. 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.
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.
Top feasts alternatives in Analytics are ranked by recent ship velocity. Browse the "feasts alternatives" section above for the current picks, or visit /alternatives/feasts for the full list with editorial commentary on each.
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.