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dbt Core vs performance

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

dbt Core vs performance: at a glance

Featuredbt Coreperformance
SectorAnalyticsAnalytics
Velocity score6.30.0
Sparks · 30d00
Top themesanalytics-engineering, dbt-fusion, adapters, clickhouser-language, model-diagnostics, bayesian, easystats
Last editorial update3h ago7d ago
WebsiteVisit →Visit →

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.

Read the full dbt Core trajectory →

What is performance?

performance keeps adding ways to check a model you have already fitted.

performance is at 0.17.1, which added check_priors() for prior predictive checks on Bayesian models and gave check_overdispersion(), check_model() and check_predictions() arguments to control residual type and plot range. The releases before it are a similar mix: a -2LL criterion column in test_likelihoodratio(), Bayesian predictive checks routed through modelbased, and in 0.16.0 a set of breaking renames including RMSA to the correct RMSR.

Read the full performance trajectory →

dbt Core vs performance: editorial side-by-side

D
dbt Core
ANALYTICS
6.3

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.

P
performance
ANALYTICS
0.0

performance keeps adding ways to check a model you have already fitted.

◆ Current state

performance is at 0.17.1, which added check_priors() for prior predictive checks on Bayesian models and gave check_overdispersion(), check_model() and check_predictions() arguments to control residual type and plot range. The releases before it are a similar mix: a -2LL criterion column in test_likelihoodratio(), Bayesian predictive checks routed through modelbased, and in 0.16.0 a set of breaking renames including RMSA to the correct RMSR.

◆ Where it's heading

Two consistent habits. Diagnostics keep gaining arguments to narrow what is examined — ppc_range, x_limits, maximum_dots, show_ci — which reads as a package being used on models large and awkward enough that the defaults stopped working. And simulated residuals via DHARMa keep displacing standard ones as the basis for the checks themselves.

◆ Prediction

With check_priors() newly added and Bayesian predictive checks now routed through modelbased, the next release most likely extends the Bayesian diagnostic set rather than reworking the frequentist checks.

Alternatives to dbt Core and performance

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 performance.

See all dbt Core alternatives → · See all performance alternatives →

Recent activity from dbt Core and performance

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

  1. 1d agodbt CoreFusion beta.2 fills in ClickHouse materializations and catalogs
  2. 5d agodbt Coredbt 1.2.7 backports the deprecated-version warning and old fixes
  3. 5d agodbt Coredbt 1.1.6 backports the deprecated-version warning and old fixes
  4. 5d agodbt Coredbt 1.3.8 backports the deprecated-version warning
  5. 5d agodbt Coredbt 1.4.10 drops Python 3.8 and warns on deprecated versions
  6. 5d agodbt Coredbt 1.5.12 drops Python 3.8 and warns on deprecated versions
  7. 1mo agoperformancecheck_priors() added; overdispersion plots use simulated residuals
  8. 2mo agoperformance-2LL criterion column and unified Bayesian predictive checks
  9. 6mo agoperformanceBreaking renames plus point-count and CI controls in check_model()
  10. 8mo agoperformancecheck_autocorrelation() methods for DHARMa objects
  11. 10mo agoperformanceFixes CRAN checks after an rstanarm update
  12. 11mo agoperformancetinytable output format in display()

Frequently asked questions

What is the difference between dbt Core and performance?

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 performance?

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 performance?

Top performance alternatives in Analytics are ranked by recent ship velocity. Browse the "performance alternatives" section above for the current picks, or visit /alternatives/easystats-performance for the full list with editorial commentary on each.