Basedash is done answering questions about your data — it now wants to tell you what to do next.
modeltime.resample alternatives
The best modeltime.resample alternatives in analytics tools, ranked by Sparkpulse's velocity_score.
Updated Aug 15, 2026
Looking for the best alternatives to modeltime.resample? Sparkpulse tracks and ranks 12 alternatives in analytics tools by shipping velocity — how frequently each ships meaningful updates, verified from official changelogs. For reference, modeltime.resample shipped 0 meaningful updates in the last 30 days and carries a velocity score of 0.0 out of 10 in 2026. The alternatives below are ranked the same way, so you're comparing real release momentum, not marketing claims.
About modeltime.resample
modeltime.resample exists to keep backtesting working as tidymodels shifts underneath it.
modeltime.resample runs time series cross-validation over modeltime models, returning per-resample predictions and accuracy plots. Version 0.3.0 is the substantive release in view: tune 2.0.0 compatibility, deterministic seeding via withr, guaranteed .predictions output, and clearer failures when resample fits break. The three releases before it are dependency chores.
Velocity 0.0 · Last update 51m ago
Top 12 alternatives to modeltime.resample
Ranked by recent ship velocity. Tap any card for the full editorial breakdown, or pivot to a head-to-head.
dbt-core spent a day backporting one deprecation warning across eight EOL branches — the message is: upgrade.
After the 836-commit 0.92 release, OpenObserve is quietly moving its MCP server into the free tier
A Bayesian real-time CFR estimator that now ships stratified fits and posterior-predictive checks
camtrapdp has become a full read-edit-write toolkit for camera trap datasets, then went quiet
spatstat's inference layer builds out determinantal and cluster process fitting
The geometry layer under spatstat, steadily absorbing 3D patterns and missing-data semantics
spatstat's simulation engine pushes point process generation into three dimensions
Clinical-table typesetting for R, closing the gap between R output and regulatory Word documents
monitOS relicenses to MIT, the clearest signal in a sparse Novartis release feed.
kernelshap makes permutation SHAP practical past eight features, then fixes the kernel weights it had wrong.
filtro moves to S7 and multiplies its feature-scoring methods in a single release.
modeltime.resample vs alternatives — shipping velocity at a glance
Velocity score (0–10) and meaningful releases shipped in the last 30 days, from official changelogs. Higher = shipping faster.
| Product | Velocity | Sparks · 30d | Focus areas | Latest release |
|---|---|---|---|---|
| modeltime.resample (baseline) | 0.0 | 0 | time seriescross-validationtidymodels | — |
| Basedash | 7.5 | 1 | ai-analystprescriptive-analyticsembedded-bi | Introducing Tasks: your operations, on autopilot |
| dbt Core | 7.5 | 0 | analytics-engineeringdeprecationbackports | — |
| OpenObserve | 6.3 | 1 | observabilitymcpopen-source | v0.92.0 adds synthetic monitoring, workflows, and AI observability |
| cfrnow | 5.0 | 0 | epidemiologybayesian-modellingcfr-estimation | First release: real-time CFR from a Bayesian mixture-cure model |
| camtrapdp | 2.5 | 0 | camera trapsbiodiversity datar | camtrapdp 0.4.0 closes the read-edit-write loop for Camtrap DP |
| spatstat.model | 2.5 | 0 | spatial-statisticspoint-processesmodel-fitting | — |
| spatstat.geom | 2.5 | 0 | spatial-statisticscomputational-geometryr-package | — |
| spatstat.random | 2.5 | 0 | spatial-statisticspoint-processessimulation | Three-dimensional point process simulation arrives |
| clinify | 2.5 | 0 | clinical-trialsr-packagedocument-generation | — |
| monitOS | 0.0 | 0 | clinical trialsoverall survivalnovartis | — |
| kernelshap | 0.0 | 0 | shapmodel explainabilitysampling algorithms | Sampling permutation SHAP with standard errors |
| filtro | 0.0 | 0 | feature selectiontidymodelss7 | Five new filter scores and the move to S7 |
The 12 best modeltime.resample alternatives, in depth
1. Basedash · velocity 7.5
Basedash is done answering questions about your data — it now wants to tell you what to do next.
Over the last 30 days Basedash shipped 1 meaningful update vs modeltime.resample's 0, most recently “Introducing Tasks: your operations, on autopilot”. Its velocity score of 7.5/10 blends that with longer-term release cadence.
Where modeltime.resample leans on time series, cross validation and tidymodels, Basedash focuses on ai analyst, prescriptive analytics and embedded bi.
Over the last 30 days Basedash has been shipping faster than modeltime.resample — a point in its favour if release momentum matters to you.
Full Basedash trajectory → · Compare modeltime.resample vs Basedash →
2. dbt Core · velocity 7.5
Dbt-core spent a day backporting one deprecation warning across eight EOL branches — the message is: upgrade.
Its velocity score of 7.5/10 reflects longer-term release cadence.
Where modeltime.resample leans on time series, cross validation and tidymodels, dbt Core focuses on analytics engineering, deprecation and backports.
dbt Core and modeltime.resample have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full dbt Core trajectory → · Compare modeltime.resample vs dbt Core →
3. OpenObserve · velocity 6.3
After the 836-commit 0.92 release, OpenObserve is quietly moving its MCP server into the free tier.
Over the last 30 days OpenObserve shipped 1 meaningful update vs modeltime.resample's 0, most recently “v0.92.0 adds synthetic monitoring, workflows, and AI observability”. Its velocity score of 6.3/10 blends that with longer-term release cadence.
Where modeltime.resample leans on time series, cross validation and tidymodels, OpenObserve focuses on observability, mcp and open source.
Over the last 30 days OpenObserve has been shipping faster than modeltime.resample — a point in its favour if release momentum matters to you.
Full OpenObserve trajectory → · Compare modeltime.resample vs OpenObserve →
4. cfrnow · velocity 5.0
A Bayesian real-time CFR estimator that now ships stratified fits and posterior-predictive checks.
Its velocity score of 5.0/10 reflects longer-term release cadence; its most recent meaningful update was “First release: real-time CFR from a Bayesian mixture-cure model”.
Where modeltime.resample leans on time series, cross validation and tidymodels, cfrnow focuses on epidemiology, bayesian modelling and cfr estimation.
cfrnow and modeltime.resample have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full cfrnow trajectory → · Compare modeltime.resample vs cfrnow →
5. camtrapdp · velocity 2.5
Camtrapdp has become a full read-edit-write toolkit for camera trap datasets, then went quiet.
Its velocity score of 2.5/10 reflects longer-term release cadence; its most recent meaningful update was “camtrapdp 0.4.0 closes the read-edit-write loop for Camtrap DP”.
Where modeltime.resample leans on time series, cross validation and tidymodels, camtrapdp focuses on camera traps, biodiversity data and r.
camtrapdp and modeltime.resample have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full camtrapdp trajectory → · Compare modeltime.resample vs camtrapdp →
6. spatstat.model · velocity 2.5
Spatstat's inference layer builds out determinantal and cluster process fitting.
Its velocity score of 2.5/10 reflects longer-term release cadence.
Where modeltime.resample leans on time series, cross validation and tidymodels, spatstat.model focuses on spatial statistics, point processes and model fitting.
spatstat.model and modeltime.resample have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full spatstat.model trajectory → · Compare modeltime.resample vs spatstat.model →
7. spatstat.geom · velocity 2.5
The geometry layer under spatstat, steadily absorbing 3D patterns and missing-data semantics.
Its velocity score of 2.5/10 reflects longer-term release cadence.
Where modeltime.resample leans on time series, cross validation and tidymodels, spatstat.geom focuses on spatial statistics, computational geometry and r package.
spatstat.geom and modeltime.resample have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full spatstat.geom trajectory → · Compare modeltime.resample vs spatstat.geom →
8. spatstat.random · velocity 2.5
Spatstat's simulation engine pushes point process generation into three dimensions.
Its velocity score of 2.5/10 reflects longer-term release cadence; its most recent meaningful update was “Three-dimensional point process simulation arrives”.
Where modeltime.resample leans on time series, cross validation and tidymodels, spatstat.random focuses on spatial statistics, point processes and simulation.
spatstat.random and modeltime.resample have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full spatstat.random trajectory → · Compare modeltime.resample vs spatstat.random →
9. clinify · velocity 2.5
Clinical-table typesetting for R, closing the gap between R output and regulatory Word documents.
Its velocity score of 2.5/10 reflects longer-term release cadence.
Where modeltime.resample leans on time series, cross validation and tidymodels, clinify focuses on clinical trials, r package and document generation.
clinify and modeltime.resample have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full clinify trajectory → · Compare modeltime.resample vs clinify →
10. monitOS · velocity 0.0
MonitOS relicenses to MIT, the clearest signal in a sparse Novartis release feed.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where modeltime.resample leans on time series, cross validation and tidymodels, monitOS focuses on clinical trials, overall survival and novartis.
monitOS and modeltime.resample have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full monitOS trajectory → · Compare modeltime.resample vs monitOS →
11. kernelshap · velocity 0.0
Kernelshap makes permutation SHAP practical past eight features, then fixes the kernel weights it had wrong.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Sampling permutation SHAP with standard errors”.
Where modeltime.resample leans on time series, cross validation and tidymodels, kernelshap focuses on shap, model explainability and sampling algorithms.
kernelshap and modeltime.resample have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full kernelshap trajectory → · Compare modeltime.resample vs kernelshap →
12. filtro · velocity 0.0
Filtro moves to S7 and multiplies its feature-scoring methods in a single release.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Five new filter scores and the move to S7”.
Where modeltime.resample leans on time series, cross validation and tidymodels, filtro focuses on feature selection, tidymodels and s7.
filtro and modeltime.resample have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full filtro trajectory → · Compare modeltime.resample vs filtro →
Frequently asked questions
What are the best alternatives to modeltime.resample?
The top modeltime.resample alternatives we currently track in analytics tools are Basedash, dbt Core, OpenObserve, cfrnow, camtrapdp, ranked by recent ship velocity.
How is this list of modeltime.resample alternatives ranked?
Alternatives are ranked by Sparkpulse's velocity_score — release cadence + 30-day spark count + sector-relative ship rate.
Can I compare modeltime.resample directly with one of these alternatives?
Yes — every card has a "Compare with modeltime.resample" link to a side-by-side /compare page.