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Comparison · Analytics
dbt Core vs hubEvals
A side-by-side editorial comparison of dbt Core and hubEvals — release velocity, themes, recent moves, and the top alternatives to consider.
dbt Core vs hubEvals: 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 hubEvals?
Forecast-hub scoring that learned to handle joint, sample-based predictions.
hubEvals scores model output from collaborative forecasting hubs, wrapping scoringutils and translating hubverse formats into forecast objects it can evaluate. The package has moved quickly from a thin translation layer to something that handles every output type the hubverse defines — quantile, mean, median, nominal and ordinal pmf, and samples. The most recent releases are almost entirely about the failure modes of relative skill scoring rather than about new metrics.
dbt Core vs hubEvals: 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.
hubEvals
2.5ANALYTICS
Forecast-hub scoring that learned to handle joint, sample-based predictions.
◆ Current state
hubEvals scores model output from collaborative forecasting hubs, wrapping scoringutils and translating hubverse formats into forecast objects it can evaluate. The package has moved quickly from a thin translation layer to something that handles every output type the hubverse defines — quantile, mean, median, nominal and ordinal pmf, and samples. The most recent releases are almost entirely about the failure modes of relative skill scoring rather than about new metrics.
◆ Where it's heading
Two threads dominate. The first is coverage of output types, which reached its widest point with sample-based and compound scoring. The second, and the one occupying every recent release, is making relative skill degrade gracefully: single-model input, comparison groups with one model, and groups missing the requested baseline have each been converted from a cryptic upstream abort into a defined result. That pattern — inherited scoringutils errors being caught and given hub-specific meaning — is the clearest signal of where this package adds value.
◆ Prediction
Expect continued work smoothing scoringutils error surfaces into hub-aware behaviour, and performance attention on relative skill, which was explicitly optimised in the latest release.
Alternatives to dbt Core and hubEvals
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 hubEvals.
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.
tulpa
The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.
AgencyAnalytics
AgencyAI got skills three weeks ago; everything since has been making them routine.
NocoDB
Interfaces gets the permissions layer it needed, one release after launching.
See all dbt Core alternatives → · See all hubEvals alternatives →
Recent activity from dbt Core and hubEvals
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
- 27d agohubEvalsScored-forecast counts and faster relative skill
- 1mo agohubEvalsDisaggregated relative skill no longer aborts the whole call
- 1mo agohubEvalsSingle-model scoring returns relative skill of 1 instead of erroring
- 5mo agohubEvalsSample output types and multivariate compound scoring ⚡
- 6mo agohubEvalsScoring on transformed scales via transform arguments
- 11mo agohubEvalsFirst release: score_model_out() and the scoringutils bridge
Frequently asked questions
What is the difference between dbt Core and hubEvals?
They serve adjacent needs but don't currently overlap on shipped themes. dbt Core is currently shipping more aggressively (velocity 6.3 vs 2.5), 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 hubEvals?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dbt Core is currently shipping more aggressively (velocity 6.3 vs 2.5), 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 hubEvals?
Top hubEvals alternatives in Analytics are ranked by recent ship velocity. Browse the "hubEvals alternatives" section above for the current picks, or visit /alternatives/hubevals for the full list with editorial commentary on each.