tidyr
tidyr replaced separate() with a family that says what it does.
Comparison · Analytics
modeltime vs Omni
A side-by-side editorial comparison of modeltime and Omni — release velocity, themes, recent moves, and the top alternatives to consider.
modeltime vs Omni: at a glance
What is modeltime?
modeltime built conformal intervals in, then went quiet on features.
modeltime is at 1.3.3, a single change making the package robust to xgboost version shifts. The feature weight sits in 1.3.2, which added a future-based parallel backend, the maape() accuracy metric and dials helpers for ADAM engine tuning, and further back in the 1.2.8 and 1.3.0 pair that introduced conformal prediction intervals and then carried them through the nested forecasting workflow.
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 seven consecutive weeks 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 support on Azure, and MCP surfaces appearing both in-app and as a searchDashboards tool. The non-AI items are steady BI plumbing — OAuth and GitHub App authentication for dbt connections, mobile dashboard settings, map legend positioning, presentation mode.
modeltime vs Omni: editorial side-by-side
modeltime
0.0ANALYTICS
modeltime built conformal intervals in, then went quiet on features.
◆ Current state
modeltime is at 1.3.3, a single change making the package robust to xgboost version shifts. The feature weight sits in 1.3.2, which added a future-based parallel backend, the maape() accuracy metric and dials helpers for ADAM engine tuning, and further back in the 1.2.8 and 1.3.0 pair that introduced conformal prediction intervals and then carried them through the nested forecasting workflow.
◆ Where it's heading
The arc runs from uncertainty quantification to execution. Conformal intervals arrived first and were then threaded through nested fitting, refitting and the printed forecast tables so users can see which confidence method produced an interval. The later work moves down a layer to how forecasts are computed — a portable future backend replacing foreach tuning — rather than what they express.
◆ Prediction
With only an xgboost compatibility fix since the 1.3.2 feature release, the entries do not support a confident prediction about what comes next beyond continued dependency maintenance.
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 seven consecutive weeks 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 support on Azure, and MCP surfaces appearing both in-app and as a searchDashboards tool. The non-AI items are steady BI plumbing — OAuth and GitHub App authentication for dbt connections, mobile dashboard settings, map legend positioning, presentation mode.
◆ Where it's heading
Two things are happening in parallel and they are related. Omni is pushing AI into the modelling layer rather than only the query layer, which is what semantic model generation reaching GA signifies — the artifact that normally takes an analytics engineer weeks is being generated. At the same time it is building the commercial and access controls that AI features require: credit limits per user and per embed entity group arrived within weeks of the AI 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.
◆ Prediction
Credit controls appearing so soon after the AI features suggests consumption limits will keep expanding to cover newer surfaces, and with searchDashboards shipped as an MCP tool, more of Omni's catalog is the obvious next thing to expose that way.
Alternatives to modeltime 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 modeltime or Omni.
performance
performance keeps adding ways to check a model you have already fitted.
cmdstanpy
CmdStanPy is clearing deprecations ahead of a 2.0 it keeps announcing.
dowhy
DoWhy adds one estimation method a year and keeps its identification edge.
OpenHouse
OpenHouse is hardening the seams where table policies and jobs quietly fail.
silx
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
See all modeltime alternatives → · See all Omni alternatives →
Recent activity from modeltime and Omni
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoOmniOmni adds presentation mode and a searchDashboards MCP tool
- 8d agoOmniOmni adds AI credit controls per user and embed entity group
- 15d agoOmniAI semantic model generation goes generally available in Omni ⚡
- 22d agoOmniOmni adds AI suggestion endpoints and OAuth for database connections
- 29d agoOmniOmni brings AI routines to Slack and adds in-app MCP settings
- 1mo agoOmniOmni adds AccessBoost for Apps and dbt deploy-token auth
- 7mo agomodeltimeRobustness to xgboost version changes
- 11mo agomodeltimefuture parallel backend, maape() metric and ADAM tuning helpers
- 2y agomodeltimeConformal intervals reach the nested forecasting workflow
- 2y agomodeltimeConformal prediction intervals introduced
- 3y agomodeltimeFixes the Smooth es() model
- 3y agomodeltimeFixes failing developer-tools tests
Frequently asked questions
What is the difference between modeltime 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 modeltime 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 modeltime?
Top modeltime alternatives in Analytics are ranked by recent ship velocity. Browse the "modeltime alternatives" section above for the current picks, or visit /alternatives/modeltime 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.