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Comparison · Infra & APIs
Depot vs FoRecoML
A side-by-side editorial comparison of Depot and FoRecoML — release velocity, themes, recent moves, and the top alternatives to consider.
Depot vs FoRecoML: at a glance
| Feature | Depot | FoRecoML |
|---|---|---|
| Sector | Infra & APIs | Infra & APIs |
| Velocity score | 6.3 | 0.0 |
| Sparks · 30d | 1 | 0 |
| Top themes | ci-cd, build-acceleration, test-intelligence, git-hosting | forecasting, machine-learning, hierarchical-reconciliation, time-series |
| Last editorial update | 5d ago | 57m ago |
| Website | — | Visit → |
What is Depot?
Depot keeps absorbing the CI stack — tests, networking, runners, now its own git host.
Depot has moved well past build caching. Test results reached general availability in July with org-wide flaky, slow, and recurring failure analytics plus timing-based shard splitting; Sherlock's AI analysis became available on any run rather than only failed ones; and CI jobs can join a Tailscale tailnet to reach private services. The runner fleet now defaults to macOS 26 on M4 hardware, Depot CI understands GitHub stacked pull requests, and Depot Code — a diskless git server backed by blob storage — entered private beta.
What is FoRecoML?
The machine-learning arm of a forecast reconciliation toolkit, four months old and already sharing its sibling's plumbing.
FoRecoML brings machine-learning approaches to forecast reconciliation across cross-sectional, temporal, and cross-temporal frameworks through csrml(), terml(), and ctrml(). It reached CRAN in April 2026 and has since spent both releases integrating with FoReco rather than expanding its own method set: results are now FoReco's foreco objects, and print() and summary() report framework, approach, problem dimensions, features, training sample size, combination matrix, and trained models.
Depot vs FoRecoML: editorial side-by-side
Depot
6.3INFRA · APIS
Depot keeps absorbing the CI stack — tests, networking, runners, now its own git host.
◆ Current state
Depot has moved well past build caching. Test results reached general availability in July with org-wide flaky, slow, and recurring failure analytics plus timing-based shard splitting; Sherlock's AI analysis became available on any run rather than only failed ones; and CI jobs can join a Tailscale tailnet to reach private services. The runner fleet now defaults to macOS 26 on M4 hardware, Depot CI understands GitHub stacked pull requests, and Depot Code — a diskless git server backed by blob storage — entered private beta.
◆ Where it's heading
The pattern is absorbing each adjacent piece of the pipeline that Depot's position already gives it data about. It runs the builds, so it owns test timing, so it can balance shards; it runs the jobs, so it can diagnose them; it hosts the runners, so it can wire private networking into them. Depot Code extends the same logic upstream to source hosting, which would close the loop between repository and runner. A quieter parallel thread keeps moving SDK- and dashboard-only settings into the CLI, stated explicitly as making projects configurable by agents and scripts.
◆ Prediction
Depot Code widening past private beta and binding more tightly to CI is the move the rest of the window sets up. The test work is also positioned to go from reporting to selection — skipping tests a change cannot affect — since Depot now holds the timing and failure history that would require, though the entries stop short of saying so.
FoRecoML
0.0INFRA · APIS
The machine-learning arm of a forecast reconciliation toolkit, four months old and already sharing its sibling's plumbing.
◆ Current state
FoRecoML brings machine-learning approaches to forecast reconciliation across cross-sectional, temporal, and cross-temporal frameworks through csrml(), terml(), and ctrml(). It reached CRAN in April 2026 and has since spent both releases integrating with FoReco rather than expanding its own method set: results are now FoReco's foreco objects, and print() and summary() report framework, approach, problem dimensions, features, training sample size, combination matrix, and trained models.
◆ Where it's heading
This package is being built as a satellite, not a competitor. Adopting FoReco's exported new_foreco_class() constructor within days of that class appearing means FoRecoML results drop straight into the same print, summary, plot, and components methods as analytically reconciled ones — which is what makes machine-learning and classical reconciliation directly comparable in a single workflow. The 1.1.1 argument-validation work landed in the same minute as the equivalent change in FoReco, so the two are being maintained as one release train.
◆ Prediction
With the integration work done, the next release is more likely to add or expose machine-learning approaches than to keep reshaping output; the structured summary already enumerates features and trained models, which suggests inspection tooling is where attention has been.
Alternatives to Depot and FoRecoML
Other Infra & APIs 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 Depot or FoRecoML.
forestploter
A forest plot package that keeps handing users control of one more graphical detail.
ggInterval
Interval-valued data plotting, spending 2026 making its function names and examples survive CRAN.
rgm
A microbiome network model that got itself un-archived by deleting the dependency that killed it.
contagionchannels
Three releases in ten days, every one of them a CRAN reviewer's correction rather than a code change.
tidyaudit
Pipeline provenance for tidyverse workflows, recording what changed at each step without keeping the data.
See all Depot alternatives → · See all FoRecoML alternatives →
Recent activity from Depot and FoRecoML
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 9d agoDepotmacOS 26 is now the default macOS version for GitHub Actions runners
- 16d agoDepotDepot CI now supports native GitHub stacked pull requests
- 19d agoDepotSet cache retention when creating a project with --cache-policy-keep-days
- 20d agoDepotView and edit project details from the Depot CLI
- 21d agoDepotTest results are now generally available ⚡
- 29d agoDepotAI analysis available for all Depot CI workflows and jobs
- 1mo agoFoRecoMLStructured print and summary for fitted reconciliation models
- 1mo agoFoRecoMLAdopts FoReco's foreco class for all reconciliation output
- 3mo agoFoRecoMLMachine-learning forecast reconciliation arrives on CRAN ⚡
Frequently asked questions
What is the difference between Depot and FoRecoML?
They serve adjacent needs but don't currently overlap on shipped themes. Depot 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 Depot better than FoRecoML?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Depot 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 Infra & APIs products to evaluate alongside.
What are the best alternatives to Depot?
Top Depot alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "Depot alternatives" section above for the current picks, or visit /alternatives/depot for the full list with editorial commentary on each.
What are the best alternatives to FoRecoML?
Top FoRecoML alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "FoRecoML alternatives" section above for the current picks, or visit /alternatives/forecoml for the full list with editorial commentary on each.