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Basedash is done answering questions about your data — it now wants to tell you what to do next.
Alternatives · analytics tools
modeltime.ensemble alternatives
The best modeltime.ensemble alternatives in analytics tools, ranked by Sparkpulse's velocity_score.
Updated Aug 15, 2026
Looking for the best alternatives to modeltime.ensemble? 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.ensemble 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.ensemble
modeltime.ensemble wakes after four years, and the work is all tune 2.0 compatibility.
modeltime.ensemble builds average, weighted and stacked ensembles over modeltime forecast models. After a four-year gap it shipped twice in a fortnight during August and September 2025, both releases devoted to tracking breaking changes in tidymodels' tune package — new resampling column conventions, key uniqueness across resamples, recipe preparation. The tidyverse dependency was dropped in the same pass.
Velocity 0.0 · Last update 52m ago
Top 12 alternatives to modeltime.ensemble
Ranked by recent ship velocity. Tap any card for the full editorial breakdown, or pivot to a head-to-head.
ANALYTICS
dbt-core spent a day backporting one deprecation warning across eight EOL branches — the message is: upgrade.
ANALYTICS
After the 836-commit 0.92 release, OpenObserve is quietly moving its MCP server into the free tier
ANALYTICS
A Bayesian real-time CFR estimator that now ships stratified fits and posterior-predictive checks
ANALYTICS
camtrapdp has become a full read-edit-write toolkit for camera trap datasets, then went quiet
ANALYTICS
spatstat's inference layer builds out determinantal and cluster process fitting
ANALYTICS
The geometry layer under spatstat, steadily absorbing 3D patterns and missing-data semantics
ANALYTICS
spatstat's simulation engine pushes point process generation into three dimensions
ANALYTICS
Clinical-table typesetting for R, closing the gap between R output and regulatory Word documents
ANALYTICS
monitOS relicenses to MIT, the clearest signal in a sparse Novartis release feed.
ANALYTICS
kernelshap makes permutation SHAP practical past eight features, then fixes the kernel weights it had wrong.
ANALYTICS
filtro moves to S7 and multiplies its feature-scoring methods in a single release.
modeltime.ensemble 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.ensemble (baseline) | 0.0 | 0 | time series forecastingensemblestidymodels | Recursive ensembles for single and panel series |
| 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.ensemble 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.ensemble'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.ensemble leans on time series forecasting, ensembles and tidymodels, Basedash focuses on ai analyst, prescriptive analytics and embedded bi.
Over the last 30 days Basedash has been shipping faster than modeltime.ensemble — a point in its favour if release momentum matters to you.
Full Basedash trajectory → · Compare modeltime.ensemble 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.ensemble leans on time series forecasting, ensembles and tidymodels, dbt Core focuses on analytics engineering, deprecation and backports.
dbt Core and modeltime.ensemble 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.ensemble 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.ensemble'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.ensemble leans on time series forecasting, ensembles and tidymodels, OpenObserve focuses on observability, mcp and open source.
Over the last 30 days OpenObserve has been shipping faster than modeltime.ensemble — a point in its favour if release momentum matters to you.
Full OpenObserve trajectory → · Compare modeltime.ensemble 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.ensemble leans on time series forecasting, ensembles and tidymodels, cfrnow focuses on epidemiology, bayesian modelling and cfr estimation.
cfrnow and modeltime.ensemble 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.ensemble 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.ensemble leans on time series forecasting, ensembles and tidymodels, camtrapdp focuses on camera traps, biodiversity data and r.
camtrapdp and modeltime.ensemble 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.ensemble 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.ensemble leans on time series forecasting, ensembles and tidymodels, spatstat.model focuses on spatial statistics, point processes and model fitting.
spatstat.model and modeltime.ensemble 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.ensemble 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.ensemble leans on time series forecasting, ensembles and tidymodels, spatstat.geom focuses on spatial statistics, computational geometry and r package.
spatstat.geom and modeltime.ensemble 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.ensemble 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.ensemble leans on time series forecasting, ensembles and tidymodels, spatstat.random focuses on spatial statistics, point processes and simulation.
spatstat.random and modeltime.ensemble 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.ensemble 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.ensemble leans on time series forecasting, ensembles and tidymodels, clinify focuses on clinical trials, r package and document generation.
clinify and modeltime.ensemble 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.ensemble 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.ensemble leans on time series forecasting, ensembles and tidymodels, monitOS focuses on clinical trials, overall survival and novartis.
monitOS and modeltime.ensemble 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.ensemble 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.ensemble leans on time series forecasting, ensembles and tidymodels, kernelshap focuses on shap, model explainability and sampling algorithms.
kernelshap and modeltime.ensemble 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.ensemble 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.ensemble leans on time series forecasting, ensembles and tidymodels, filtro focuses on feature selection, tidymodels and s7.
filtro and modeltime.ensemble 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.ensemble vs filtro →
Frequently asked questions
What are the best alternatives to modeltime.ensemble?
The top modeltime.ensemble 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.ensemble alternatives ranked?
Alternatives are ranked by Sparkpulse's velocity_score — release cadence + 30-day spark count + sector-relative ship rate.
Can I compare modeltime.ensemble directly with one of these alternatives?
Yes — every card has a "Compare with modeltime.ensemble" link to a side-by-side /compare page.