chattr deleted every LLM integration it had written and outsourced the lot to ellmer
brulee alternatives
The best brulee alternatives in analytics tools, ranked by Sparkpulse's velocity_score.
Updated Aug 14, 2026
Looking for the best alternatives to brulee? Sparkpulse tracks and ranks 12 alternatives in analytics tools by shipping velocity — how frequently each ships meaningful updates, verified from official changelogs. For reference, brulee 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 brulee
tidymodels' torch backend grew from MLPs into a tabular deep learning suite with foundation models.
brulee fits neural networks for tidymodels on torch, and 1.0.0 redefined what that means: alongside the original MLP it now ships Regularization Learning Networks, ResNet with skip connections and batch normalization, AutoInt with columnwise attention, SAINT with row and column attention, and Chronos2, a foundational forecasting model. GPU acceleration arrived in the same release with automatic CUDA selection and opt-in MPS. Version 1.1.0 added TabICL, an open-source tabular foundation model, and 1.1.1 spent its time cleaning up the consequences of shipping models that need weight downloads.
Velocity 0.0 · Last update 2h ago
Top 12 alternatives to brulee
Ranked by recent ship velocity. Tap any card for the full editorial breakdown, or pivot to a head-to-head.
Six years since the last functional change, and Google renamed the service it wraps in the release before that
The meta-package ships almost nothing, which is exactly what a version-pinning shim should do
The DataONE bundler learned to edit packages in 2017 and has coasted on that ever since
Seven years dormant, then two releases dragging every census boundary from 2020 to 2024
Feature-complete since 2021, and every release since has been paying CRAN's C API bill
A fixed-design trial simulator grew a pluggable test framework, then spent a year proving the numbers
One document API over six databases, and every release is spent absorbing their JSON engines' churn
Sparse vectors stopped being a storage trick and became something you can do arithmetic on
A Darwin Core validator that went quiet for two years, then surfaced only to raise its R floor
Four releases in three years, each one teaching the serializer about a model type it couldn't carry
The R port of LIME has shipped one commit in three years, and it was an xgboost compatibility patch
brulee 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 |
|---|---|---|---|---|
| brulee (baseline) | 0.0 | 0 | deep-learningtabular-modelstorch | Five new architectures and GPU support arrive at 1.0.0 |
| chattr | 0.0 | 0 | llmrstudioide-integration | All model integration moves to ellmer, direct backends removed |
| cloudml | 0.0 | 0 | machine-learninggoogle-cloudtensorflow | — |
| tidymodels | 0.0 | 0 | tidymodelsmeta-packagedependency-management | — |
| datapack | 0.0 | 0 | research-datadataoneprovenance | Assembled data packages become editable in place |
| USAboundaries | 0.0 | 0 | geospatialcensus-datasf | Data split into a companion package; all boundaries become sf |
| slider | 0.0 | 0 | sliding-windowstidyversec-api-compliance | — |
| simtrial | 0.0 | 0 | clinical-trialsgroup-sequentialsurvival-analysis | RMST and milestone tests, plus a user-definable cut and test framework |
| nodbi | 0.0 | 0 | document-databasesjsonduckdb | Query results get consistent column types; fast NDJSON import reaches SQLite and Postgres |
| sparsevctrs | 0.0 | 0 | sparse-datatidymodelsaltrep | Scalar and element-wise arithmetic for sparse vectors |
| dwctaxon | 0.0 | 0 | darwin-coretaxonomydata-validation | — |
| bundle | 0.0 | 0 | serializationtidymodelsmodel-deployment | — |
| lime | 0.0 | 0 | explainabilitymachine-learningmaintenance-mode | — |
The 12 best brulee alternatives, in depth
1. chattr · velocity 0.0
Chattr deleted every LLM integration it had written and outsourced the lot to ellmer.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “All model integration moves to ellmer, direct backends removed”.
Where brulee leans on deep learning, tabular models and torch, chattr focuses on llm, rstudio and ide integration.
chattr and brulee have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
2. cloudml · velocity 0.0
Six years since the last functional change, and Google renamed the service it wraps in the release before that.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where brulee leans on deep learning, tabular models and torch, cloudml focuses on machine learning, google cloud and tensorflow.
cloudml and brulee have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
3. tidymodels · velocity 0.0
The meta-package ships almost nothing, which is exactly what a version-pinning shim should do.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where brulee leans on deep learning, tabular models and torch, tidymodels focuses on tidymodels, meta package and dependency management.
tidymodels and brulee have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full tidymodels trajectory → · Compare brulee vs tidymodels →
4. datapack · velocity 0.0
The DataONE bundler learned to edit packages in 2017 and has coasted on that ever since.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Assembled data packages become editable in place”.
Where brulee leans on deep learning, tabular models and torch, datapack focuses on research data, dataone and provenance.
datapack and brulee have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
5. USAboundaries · velocity 0.0
Seven years dormant, then two releases dragging every census boundary from 2020 to 2024.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Data split into a companion package; all boundaries become sf”.
Where brulee leans on deep learning, tabular models and torch, USAboundaries focuses on geospatial, census data and sf.
USAboundaries and brulee have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full USAboundaries trajectory → · Compare brulee vs USAboundaries →
6. slider · velocity 0.0
Feature-complete since 2021, and every release since has been paying CRAN's C API bill.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where brulee leans on deep learning, tabular models and torch, slider focuses on sliding windows, tidyverse and c api compliance.
slider and brulee have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
7. simtrial · velocity 0.0
A fixed-design trial simulator grew a pluggable test framework, then spent a year proving the numbers.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “RMST and milestone tests, plus a user-definable cut and test framework”.
Where brulee leans on deep learning, tabular models and torch, simtrial focuses on clinical trials, group sequential and survival analysis.
simtrial and brulee have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
8. nodbi · velocity 0.0
One document API over six databases, and every release is spent absorbing their JSON engines' churn.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Query results get consistent column types; fast NDJSON import reaches SQLite and Postgres”.
Where brulee leans on deep learning, tabular models and torch, nodbi focuses on document databases, json and duckdb.
nodbi and brulee have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
9. sparsevctrs · velocity 0.0
Sparse vectors stopped being a storage trick and became something you can do arithmetic on.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Scalar and element-wise arithmetic for sparse vectors”.
Where brulee leans on deep learning, tabular models and torch, sparsevctrs focuses on sparse data, tidymodels and altrep.
sparsevctrs and brulee have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full sparsevctrs trajectory → · Compare brulee vs sparsevctrs →
10. dwctaxon · velocity 0.0
A Darwin Core validator that went quiet for two years, then surfaced only to raise its R floor.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where brulee leans on deep learning, tabular models and torch, dwctaxon focuses on darwin core, taxonomy and data validation.
dwctaxon and brulee have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
11. bundle · velocity 0.0
Four releases in three years, each one teaching the serializer about a model type it couldn't carry.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where brulee leans on deep learning, tabular models and torch, bundle focuses on serialization, tidymodels and model deployment.
bundle and brulee have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
12. lime · velocity 0.0
The R port of LIME has shipped one commit in three years, and it was an xgboost compatibility patch.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where brulee leans on deep learning, tabular models and torch, lime focuses on explainability, machine learning and maintenance mode.
lime and brulee have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Frequently asked questions
What are the best alternatives to brulee?
The top brulee alternatives we currently track in analytics tools are chattr, cloudml, tidymodels, datapack, USAboundaries, ranked by recent ship velocity.
How is this list of brulee alternatives ranked?
Alternatives are ranked by Sparkpulse's velocity_score — release cadence + 30-day spark count + sector-relative ship rate.
Can I compare brulee directly with one of these alternatives?
Yes — every card has a "Compare with brulee" link to a side-by-side /compare page.