modeltime
modeltime built conformal intervals in, then went quiet on features.
A side-by-side editorial comparison of dbt Core and tidyr — release velocity, themes, recent moves, and the top alternatives to consider.
The Rust rewrite crosses from alpha to beta, and it can now bind SQL without touching the warehouse.
dbt is running two release lines at once. The 1.x Python line reached 1.12.0 in July, a GA that removed the experimental dbt login command and the bundled dbt-state plugin outright while adding the v2 semantic layer YAML parsing. The 2.0 Fusion line — the Rust engine — moved through five alphas and reached its first beta on August 10, carrying catalog-free binding, dbt state explain, redundant-test skipping, and a lint rule system that understands node selection.
tidyr replaced separate() with a family that says what it does.
tidyr is at 1.3.2, a collection of argument additions — fill() gains .by, expand_grid() gains .vary — and better error messages around unchop() and pivot_wider_spec(). The structural work is 1.3.0, which introduced separate_wider_delim(), separate_wider_position(), separate_wider_regex(), separate_longer_delim() and separate_longer_position() as thorough replacements for separate(), extract() and separate_rows().
dbt is running two release lines at once. The 1.x Python line reached 1.12.0 in July, a GA that removed the experimental dbt login command and the bundled dbt-state plugin outright while adding the v2 semantic layer YAML parsing. The 2.0 Fusion line — the Rust engine — moved through five alphas and reached its first beta on August 10, carrying catalog-free binding, dbt state explain, redundant-test skipping, and a lint rule system that understands node selection.
Fusion is being built to do statically what dbt-core did by asking the warehouse. Catalog-free binding lets SQL bind without introspection, tests get skipped when they are provably redundant, and dbt State speculatively submits nodes while the dependency prefetch is still in flight — all of it trading round-trips for compile-time analysis. Meanwhile 1.x is absorbing the v2 semantic layer YAML piece by piece, which puts metrics and entities into the model graph itself. Adapter breadth keeps widening in parallel, with Databricks service principal auth, Redshift group grants, and ClickHouse materialization configs.
With beta.1 out, the next milestones are further betas hardening the Fusion feature set toward parity, and continued v2 semantic YAML work landing in the 1.x line.
tidyr is at 1.3.2, a collection of argument additions — fill() gains .by, expand_grid() gains .vary — and better error messages around unchop() and pivot_wider_spec(). The structural work is 1.3.0, which introduced separate_wider_delim(), separate_wider_position(), separate_wider_regex(), separate_longer_delim() and separate_longer_position() as thorough replacements for separate(), extract() and separate_rows().
Two habits define this window. Verbs are being split into explicitly named variants rather than overloaded with arguments, which is what the separate_* family does to separate(). And .by is spreading as the standard way to express grouping inline — nest(.by=) in 1.3.0, fill(.by=) in 1.3.2 — pulling users away from wrapping calls in group_by().
Given that .by has now reached fill() and nest(), the next release most likely extends the same argument to further verbs rather than reworking another function family.
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 tidyr.
modeltime built conformal intervals in, then went quiet on features.
performance keeps adding ways to check a model you have already fitted.
CmdStanPy is clearing deprecations ahead of a 2.0 it keeps announcing.
DoWhy adds one estimation method a year and keeps its identification edge.
OpenHouse is hardening the seams where table policies and jobs quietly fail.
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
See all dbt Core alternatives → · See all tidyr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. dbt Core is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 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. dbt Core is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 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 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.
Top tidyr alternatives in Analytics are ranked by recent ship velocity. Browse the "tidyr alternatives" section above for the current picks, or visit /alternatives/tidyr for the full list with editorial commentary on each.