tidyr
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Comparison · Analytics
Appfigures vs modeltime
A side-by-side editorial comparison of Appfigures and modeltime — release velocity, themes, recent moves, and the top alternatives to consider.
Appfigures vs modeltime: at a glance
| Feature | Appfigures | modeltime |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 3.8 | 0.0 |
| Sparks · 30d | 1 | 0 |
| Top themes | app-analytics, agentic, aso, competitive-intelligence | forecasting, conformal-prediction, tidymodels, parallelism |
| Last editorial update | 1d ago | 1h ago |
| Website | — | Visit → |
What is Appfigures?
Appfigures just made its app-market data something an AI agent can query, not something you screenshot.
Appfigures has spent the last year widening what its estimates cover — iPad data folded into every download and revenue figure, state-level financials in the API, a 15-report App Intelligence suite for competitor research, and Leaderboards that rank apps by explicit metrics instead of opaque store charts. The August release changes who consumes all of that: a CLI built specifically for AI agents, with a hinting system to keep them from misreading the data. The product is no longer only a dashboard.
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.
Appfigures vs modeltime: editorial side-by-side
Appfigures
3.8ANALYTICS
Appfigures just made its app-market data something an AI agent can query, not something you screenshot.
◆ Current state
Appfigures has spent the last year widening what its estimates cover — iPad data folded into every download and revenue figure, state-level financials in the API, a 15-report App Intelligence suite for competitor research, and Leaderboards that rank apps by explicit metrics instead of opaque store charts. The August release changes who consumes all of that: a CLI built specifically for AI agents, with a hinting system to keep them from misreading the data. The product is no longer only a dashboard.
◆ Where it's heading
The arc runs from data completeness to data access. First they closed gaps in the underlying estimates, then they built more ways to slice them, and now they are exposing the whole surface to agents that can investigate, compare, monitor, and act — including replying to reviews and adjusting Apple Ads campaigns. Each layer assumes the one below it is trustworthy, which is why the accuracy fixes (iPad coverage, keyword popularity, Google Play delay removal) came first.
◆ Prediction
Expect the agent surface to deepen before it widens — more write actions exposed through the CLI, and Leaderboards and App Intelligence reports made directly queryable by agents rather than only through the web reports.
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.
Alternatives to Appfigures and modeltime
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 Appfigures or modeltime.
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 Appfigures alternatives → · See all modeltime alternatives →
Recent activity from Appfigures and modeltime
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoAppfiguresIntroducing the Appfigures CLI ⚡
- 1mo agoAppfiguresIntroducing Appfigures Leaderboards
- 3mo agoAppfiguresApp Intelligence for iPad
- 7mo agomodeltimeRobustness to xgboost version changes
- 8mo agoAppfiguresSupport for By State Financial Reports via the API
- 8mo agoAppfiguresDaily Averages Across Reports
- 8mo agoAppfiguresIntroducing the New App Intelligence ⚡
- 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 Appfigures and modeltime?
They serve adjacent needs but don't currently overlap on shipped themes. Appfigures is currently shipping more aggressively (velocity 3.8 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 Appfigures better than modeltime?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Appfigures is currently shipping more aggressively (velocity 3.8 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 Appfigures?
Top Appfigures alternatives in Analytics are ranked by recent ship velocity. Browse the "Appfigures alternatives" section above for the current picks, or visit /alternatives/appfigures for the full list with editorial commentary on each.
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.