distributions3
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
Comparison · Analytics
dbt Core vs fastglm
A side-by-side editorial comparison of dbt Core and fastglm — release velocity, themes, recent moves, and the top alternatives to consider.
dbt Core vs fastglm: at a glance
What is dbt Core?
dbt Fusion's second beta is adapter work: ClickHouse gets materializations, indexes, and catalogs
Fusion 2.0 is in its second beta, and the content has shifted from engine capability to adapter coverage. beta.2 is almost entirely ClickHouse — Dictionary materialization, index definitions, additional settings, a relation-scoped catalog macro that fixes --write-catalog, and a seed nullability fix — plus Entra bearer-token authentication for the Fabric adapter. Behind it sits the August 14 backport wave, which cut releases for 1.1 through 1.8 in a single day to deliver one deprecated-version warning.
What is fastglm?
A fast GLM solver stops being one function and becomes a count-model family
fastglm ran C++ IRLS for standard generalized linear models for six years with almost no releases. In May 2026 it added three top-level model types — negative binomial with jointly estimated dispersion, hurdle, and zero-inflated — each with the entire fitting driver in C++ rather than an R loop around a C++ kernel. The following release generalised Firth bias reduction to every standard family across dense, sparse and streaming backends.
dbt Core vs fastglm: editorial side-by-side
dbt Core
6.3ANALYTICS
dbt Fusion's second beta is adapter work: ClickHouse gets materializations, indexes, and catalogs
◆ Current state
Fusion 2.0 is in its second beta, and the content has shifted from engine capability to adapter coverage. beta.2 is almost entirely ClickHouse — Dictionary materialization, index definitions, additional settings, a relation-scoped catalog macro that fixes --write-catalog, and a seed nullability fix — plus Entra bearer-token authentication for the Fabric adapter. Behind it sits the August 14 backport wave, which cut releases for 1.1 through 1.8 in a single day to deliver one deprecated-version warning.
◆ Where it's heading
The two ends of this project are pulling apart cleanly. Old branches are being prepared for retirement — a deprecation warning fanned across eight of them, Python 3.8 testing dropped from 1.4 through 1.6 — while Fusion accumulates the adapter breadth it needs to be a credible replacement. beta.1 proved the engine could bind without a catalog; beta.2 is the unglamorous follow-through of making a specific warehouse work properly.
◆ Prediction
Expect further beta releases filling in per-adapter gaps rather than new engine capability, and formal end-of-life notices for the branches that just took the deprecation warning.
fastglm
0.0ANALYTICS
A fast GLM solver stops being one function and becomes a count-model family
◆ Current state
fastglm ran C++ IRLS for standard generalized linear models for six years with almost no releases. In May 2026 it added three top-level model types — negative binomial with jointly estimated dispersion, hurdle, and zero-inflated — each with the entire fitting driver in C++ rather than an R loop around a C++ kernel. The following release generalised Firth bias reduction to every standard family across dense, sparse and streaming backends.
◆ Where it's heading
The package changed what it is. Through 0.0.3 it was a drop-in replacement for glm() competing on speed; from 0.1.0 it targets the models people leave base R for — MASS::glm.nb, pscl::hurdle, pscl::zeroinfl — and reimplements their full estimation loops natively. The 0.1.1 follow-up is consolidation on that new surface: Firth generalised past binomial logit, SQUAREM acceleration on the zero-inflation EM driver, and a run of clamping guards and initialization fixes on the families most prone to overflow.
◆ Prediction
The numerical-stability work in 0.1.1 clusters on Tweedie and the inverse and sqrt link families, which suggests those paths are the newest and least exercised — expect further correctness fixes there before new model types.
Alternatives to dbt Core and fastglm
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 dbt Core or fastglm.
Basedash
Basedash keeps pushing its data out of the workspace — now to people without accounts
RStudio
RStudio ships through release branches, and the notes are commit messages
Fulcrum
Fulcrum is betting its whole map stack on Esri, with a hard Google Maps cutoff on September 1.
Holistics
Holistics keeps fencing in the AI layer it spent the summer building.
Dovetail
Dovetail spent July opening doors to other tools and August making its own rooms easier to enter.
See all dbt Core alternatives → · See all fastglm alternatives →
Recent activity from dbt Core and fastglm
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agodbt CoreFusion beta.2 fills in ClickHouse materializations and catalogs
- 5d agodbt Coredbt 1.2.7 backports the deprecated-version warning and old fixes
- 5d agodbt Coredbt 1.1.6 backports the deprecated-version warning and old fixes
- 5d agodbt Coredbt 1.3.8 backports the deprecated-version warning
- 5d agodbt Coredbt 1.4.10 drops Python 3.8 and warns on deprecated versions
- 5d agodbt Coredbt 1.5.12 drops Python 3.8 and warns on deprecated versions
- 2mo agofastglmFirth generalised to all families, plus SQUAREM and stability fixes
- 3mo agofastglmCRAN release 0.1.0 ⚡
- 4y agofastglmC++ headers exposed for linking
- 7y agofastglmFirst CRAN release of the C++ IRLS solver
Frequently asked questions
What is the difference between dbt Core and fastglm?
They serve adjacent needs but don't currently overlap on shipped themes. dbt Core is currently shipping more aggressively (velocity 6.3 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 dbt Core better than fastglm?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dbt Core is currently shipping more aggressively (velocity 6.3 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 dbt Core?
Top dbt Core alternatives in Analytics are ranked by recent ship velocity. Browse the "dbt Core alternatives" section above for the current picks, or visit /alternatives/dbt-core for the full list with editorial commentary on each.
What are the best alternatives to fastglm?
Top fastglm alternatives in Analytics are ranked by recent ship velocity. Browse the "fastglm alternatives" section above for the current picks, or visit /alternatives/fastglm for the full list with editorial commentary on each.