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Comparison · Analytics
performance vs Omni
A side-by-side editorial comparison of performance and Omni — release velocity, themes, recent moves, and the top alternatives to consider.
performance vs Omni: at a glance
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.
What is Omni?
Omni ships weekly, and almost every week the headline item is an AI feature.
Omni publishes a dated weekly digest whose body is a single line listing that week's items, so each entry compresses several releases into a sentence. Across the window the pattern is unmistakable: AI-powered semantic model generation reaching general availability, AI Routines creatable from chat and deliverable to Slack, AI model suggestion endpoints, AI credit controls scoped to embed entity groups and individual users, AI Evals on Azure, and MCP surfaces appearing both in-app and as a searchDashboards tool. The most recent week breaks that streak — default filters on composite topics, stopping a running dashboard query, full-screen preview editing — the first digest in two months led by conventional BI work.
performance vs Omni: editorial side-by-side
performance
0.0ANALYTICS
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.
Omni
6.3ANALYTICS
Omni ships weekly, and almost every week the headline item is an AI feature.
◆ Current state
Omni publishes a dated weekly digest whose body is a single line listing that week's items, so each entry compresses several releases into a sentence. Across the window the pattern is unmistakable: AI-powered semantic model generation reaching general availability, AI Routines creatable from chat and deliverable to Slack, AI model suggestion endpoints, AI credit controls scoped to embed entity groups and individual users, AI Evals on Azure, and MCP surfaces appearing both in-app and as a searchDashboards tool. The most recent week breaks that streak — default filters on composite topics, stopping a running dashboard query, full-screen preview editing — the first digest in two months led by conventional BI work.
◆ Where it's heading
Two things have been happening in parallel and they are related. Omni pushed AI into the modelling layer rather than only the query layer, which is what semantic model generation reaching GA signified, then built the commercial and access controls those features require — credit limits per user and per embed entity group arrived within weeks of the capabilities that consume them. The MCP work points at a third direction, exposing Omni's content to external agents rather than only serving its own chat. The latest week's return to filters and query controls suggests the AI surface has reached the point where the surrounding product has to catch up to it.
◆ Prediction
With searchDashboards already shipped as an MCP tool, more of Omni's catalog is the obvious next thing to expose that way, and credit controls should keep extending to cover newer AI surfaces. Whether the non-AI week is a pause or a genuine rebalancing is not something one digest can settle.
Alternatives to performance and Omni
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 performance or Omni.
silx
silx settles into maintenance a release after its PySide6 migration
Plotly
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
aniread
aniread stops asking you to know which tracker wrote the file
Rho
Rho's release machinery finally produced a stable build — and it shipped no new product.
Usermaven
Usermaven closed the loop: data comes in from anywhere, and now it goes back out.
See all performance alternatives → · See all Omni alternatives →
Recent activity from performance and Omni
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 16h agoOmniOmni adds default filters on composite topics and query stopping
- 8d agoOmniOmni adds presentation mode and a searchDashboards MCP tool
- 15d agoOmniOmni adds AI credit controls per user and embed entity group
- 22d agoOmniAI semantic model generation goes generally available in Omni ⚡
- 29d agoOmniOmni adds AI suggestion endpoints and OAuth for database connections
- 1mo agoOmniOmni brings AI routines to Slack and adds in-app MCP settings
- 1mo agoperformancecheck_priors() added; overdispersion plots use simulated residuals
- 2mo agoperformance-2LL criterion column and unified Bayesian predictive checks
- 6mo agoperformanceBreaking renames plus point-count and CI controls in check_model()
- 8mo agoperformancecheck_autocorrelation() methods for DHARMa objects
- 10mo agoperformanceFixes CRAN checks after an rstanarm update
- 11mo agoperformancetinytable output format in display()
Frequently asked questions
What is the difference between performance and Omni?
They serve adjacent needs but don't currently overlap on shipped themes. Omni is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 performance better than Omni?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Omni is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 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.
What are the best alternatives to Omni?
Top Omni alternatives in Analytics are ranked by recent ship velocity. Browse the "Omni alternatives" section above for the current picks, or visit /alternatives/omni for the full list with editorial commentary on each.