← Back to home
Comparison · Analytics

Delta Lake vs fastglm

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

Delta Lake vs fastglm: at a glance

FeatureDelta Lakefastglm
SectorAnalyticsAnalytics
Velocity score5.00.0
Sparks · 30d00
Top themeslakehouse, transaction-log, delta-sharing, kernelstatistical-computing, generalized-linear-models, cpp, r-package
Last editorial update1h ago2d ago
WebsiteVisit →Visit →

What is Delta Lake?

A 4.4.0 tag appears, but the feed carries only its release plumbing

The newest entry is the commit that tagged 4.4.0 — a version.sbt bump plus a local Maven overwrite setting needed for cross-Spark publishing, and it states outright that there are no runtime behaviour changes. The 4.4.0 release notes themselves have not reached this feed, so what the minor version actually contains is not readable here. Behind it sit two patch releases doing targeted correctness work: 3.3.3 on transaction log retention and Delta Sharing cache, 4.3.1 on Delta REST Catalog OAuth and S3A listing, interleaved with near-daily Databricks kernel build tags.

Read the full Delta Lake trajectory →

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.

Read the full fastglm trajectory →

Delta Lake vs fastglm: editorial side-by-side

D
Delta Lake
ANALYTICS
5.0

A 4.4.0 tag appears, but the feed carries only its release plumbing

◆ Current state

The newest entry is the commit that tagged 4.4.0 — a version.sbt bump plus a local Maven overwrite setting needed for cross-Spark publishing, and it states outright that there are no runtime behaviour changes. The 4.4.0 release notes themselves have not reached this feed, so what the minor version actually contains is not readable here. Behind it sit two patch releases doing targeted correctness work: 3.3.3 on transaction log retention and Delta Sharing cache, 4.3.1 on Delta REST Catalog OAuth and S3A listing, interleaved with near-daily Databricks kernel build tags.

◆ Where it's heading

The project keeps two supported lines stable in parallel while the format work happens elsewhere, and the durable theme across these patches is metadata and log correctness — the failures that silently break time travel and CDF rather than throwing. The 4.4.0 prep notes one thing worth watching: artifacts are now published across Spark 4.0, 4.1 and 4.2 stages, so the cross-Spark support matrix is widening even as the release content stays out of view.

◆ Prediction

The 4.4.0 release notes should follow this tag and reveal what the minor version carries; until they do the entries support no read on its direction. The unresolved delta-iceberg artifact gap on the 3.3 line still has no follow-up here.

F
fastglm
ANALYTICS
0.0

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 Delta Lake 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 Delta Lake or fastglm.

See all Delta Lake alternatives → · See all fastglm alternatives →

Recent activity from Delta Lake and fastglm

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

  1. 7h agoDelta Lake4.4.0 release-prep tag: version bump, no runtime changes
  2. 7d agoDelta LakeLog-retention and Delta Sharing cache fixes; UniForm jar not published
  3. 20d agoDelta LakeDatabricks kernel build tag (2026-07-30)
  4. 1mo agoDelta LakeKernel build tag: _last_checkpoint captured as opaque JSON
  5. 1mo agoDelta Lake4.3.1 fixes Delta REST Catalog OAuth and S3A fast listing
  6. 1mo agoDelta LakeDatabricks kernel build tag (2026-07-07)
  7. 2mo agofastglmFirth generalised to all families, plus SQUAREM and stability fixes
  8. 3mo agofastglmCRAN release 0.1.0
  9. 4y agofastglmC++ headers exposed for linking
  10. 7y agofastglmFirst CRAN release of the C++ IRLS solver

Frequently asked questions

What is the difference between Delta Lake and fastglm?

They serve adjacent needs but don't currently overlap on shipped themes. Delta Lake 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 Delta Lake better than fastglm?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Delta Lake 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 Delta Lake?

Top Delta Lake alternatives in Analytics are ranked by recent ship velocity. Browse the "Delta Lake alternatives" section above for the current picks, or visit /alternatives/delta-lake 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.