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poissonreg vs TimescaleDB

A side-by-side editorial comparison of poissonreg and TimescaleDB — release velocity, themes, recent moves, and the top alternatives to consider.

poissonreg vs TimescaleDB: at a glance

FeaturepoissonregTimescaleDB
SectorAnalyticsAnalytics
Velocity score0.05.0
Sparks · 30d00
Top themestidymodels, count-regression, glmnet, r-languagetime-series, postgresql, columnstore, query-optimization
Last editorial update4d ago1d ago
WebsiteVisit →Visit →

What is poissonreg?

poissonreg gave its models away to parsnip and kept the glue — now it just keeps glmnet honest.

poissonreg is a tidymodels extension that wires Poisson and zero-inflated count regression into the parsnip interface. Its defining event was giving up ownership: the model definition functions moved into parsnip itself, leaving this package as engine bindings and prediction plumbing. The current dev release is entirely correctness and hygiene work — glmnet predictions now default to mean counts rather than the linear predictor, and single-observation prediction works at last.

Read the full poissonreg trajectory →

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.

Read the full TimescaleDB trajectory →

poissonreg vs TimescaleDB: editorial side-by-side

P
poissonreg
ANALYTICS
0.0

poissonreg gave its models away to parsnip and kept the glue — now it just keeps glmnet honest.

◆ Current state

poissonreg is a tidymodels extension that wires Poisson and zero-inflated count regression into the parsnip interface. Its defining event was giving up ownership: the model definition functions moved into parsnip itself, leaving this package as engine bindings and prediction plumbing. The current dev release is entirely correctness and hygiene work — glmnet predictions now default to mean counts rather than the linear predictor, and single-observation prediction works at last.

◆ Where it's heading

Release cadence has collapsed from yearly to a four-year gap between 1.0.1 and the current development version, and the content has shifted from features to deduplication against parsnip — copied helper functions replaced by the upstream originals, obsolete generic registrations removed, tests migrated to the shared extension-package pattern. This is what a stabilized tidymodels satellite looks like: the interface lives upstream, and the package's job is to not drift from it.

◆ Prediction

The dev version's accumulated fixes point to a CRAN release of 1.0.2 as the next move, with content limited to the glmnet prediction corrections rather than any new engine or model type.

T
TimescaleDB
ANALYTICS
5.0

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 poissonreg 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 poissonreg or TimescaleDB.

See all poissonreg alternatives → · See all TimescaleDB alternatives →

Recent activity from poissonreg and TimescaleDB

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1d agoTimescaleDB2.29.2: SkipScan and sparse-index correctness fixes
  2. 15d agoTimescaleDB2.29.1: security fixes plus compression bugfixes
  3. 19d agoTimescaleDB2.29.0: chunk exclusion speeds up UPDATE and DELETE
  4. 1mo agoTimescaleDB2.28.3: columnar pipeline correctness fixes
  5. 1mo agoTimescaleDB2.28.2: upgrade-path fixes for 2.28.1
  6. 1mo agoTimescaleDB2.28.1: compressed-table crash and constraint fixes
  7. 4mo agopoissonregglmnet predictions now default to mean counts
  8. 3y agopoissonregDocumentation regenerated for valid HTML5
  9. 4y agopoissonregCase weight support tracks parsnip 1.0.0
  10. 4y agopoissonregModel definitions move out of poissonreg into parsnip
  11. 5y agopoissonregglm becomes the default engine; tidy() for hurdle models
  12. 5y agopoissonregFirst release, with a glmnet column-order safeguard

Frequently asked questions

What is the difference between poissonreg 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 poissonreg 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 poissonreg?

Top poissonreg alternatives in Analytics are ranked by recent ship velocity. Browse the "poissonreg alternatives" section above for the current picks, or visit /alternatives/poissonreg 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.