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chattr deleted every LLM integration it had written and outsourced the lot to ellmer
Alternatives · analytics tools
rbmi alternatives
The best rbmi alternatives in analytics tools, ranked by Sparkpulse's velocity_score.
Updated Aug 14, 2026
Looking for the best alternatives to rbmi? Sparkpulse tracks and ranks 12 alternatives in analytics tools by shipping velocity — how frequently each ships meaningful updates, verified from official changelogs. For reference, rbmi shipped 0 meaningful updates in the last 30 days and carries a velocity score of 2.5 out of 10 in 2026. The alternatives below are ranked the same way, so you're comparing real release momentum, not marketing claims.
About rbmi
Reference-based multiple imputation for trials, now shipping without Bayesian support by default.
rbmi implements reference-based multiple imputation for longitudinal clinical trial data with missing values — the estimand machinery regulators expect for handling intercurrent events and dropout. The consequential recent change was 1.3.0 moving rstan from a hard dependency to Suggests, which takes Bayesian imputation out of the default install. Since then the work has been documentation and nomenclature discipline: 1.6.1 standardized on MNAR over a mixed NMAR/MNAR vocabulary and deprecated the nmar.rm argument accordingly.
Velocity 2.5 · Last update 2h ago
Top 12 alternatives to rbmi
Ranked by recent ship velocity. Tap any card for the full editorial breakdown, or pivot to a head-to-head.
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Six years since the last functional change, and Google renamed the service it wraps in the release before that
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The meta-package ships almost nothing, which is exactly what a version-pinning shim should do
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The DataONE bundler learned to edit packages in 2017 and has coasted on that ever since
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Seven years dormant, then two releases dragging every census boundary from 2020 to 2024
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Feature-complete since 2021, and every release since has been paying CRAN's C API bill
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A fixed-design trial simulator grew a pluggable test framework, then spent a year proving the numbers
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One document API over six databases, and every release is spent absorbing their JSON engines' churn
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Sparse vectors stopped being a storage trick and became something you can do arithmetic on
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A Darwin Core validator that went quiet for two years, then surfaced only to raise its R floor
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Four releases in three years, each one teaching the serializer about a model type it couldn't carry
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The R port of LIME has shipped one commit in three years, and it was an xgboost compatibility patch
rbmi 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 |
|---|---|---|---|---|
| rbmi (baseline) | 2.5 | 0 | clinical-trialsmissing-datamultiple-imputation | rstan demoted to Suggests, Bayesian imputation now opt-in |
| 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 rbmi 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 rbmi leans on clinical trials, missing data and multiple imputation, chattr focuses on llm, rstudio and ide integration.
chattr and rbmi 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 rbmi leans on clinical trials, missing data and multiple imputation, cloudml focuses on machine learning, google cloud and tensorflow.
cloudml and rbmi 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 rbmi leans on clinical trials, missing data and multiple imputation, tidymodels focuses on tidymodels, meta package and dependency management.
tidymodels and rbmi have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
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 rbmi leans on clinical trials, missing data and multiple imputation, datapack focuses on research data, dataone and provenance.
datapack and rbmi 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 rbmi leans on clinical trials, missing data and multiple imputation, USAboundaries focuses on geospatial, census data and sf.
USAboundaries and rbmi 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 rbmi 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 rbmi leans on clinical trials, missing data and multiple imputation, slider focuses on sliding windows, tidyverse and c api compliance.
slider and rbmi 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 rbmi leans on clinical trials, missing data and multiple imputation, simtrial focuses on clinical trials, group sequential and survival analysis.
simtrial and rbmi 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 rbmi leans on clinical trials, missing data and multiple imputation, nodbi focuses on document databases, json and duckdb.
nodbi and rbmi 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 rbmi leans on clinical trials, missing data and multiple imputation, sparsevctrs focuses on sparse data, tidymodels and altrep.
sparsevctrs and rbmi 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 rbmi 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 rbmi leans on clinical trials, missing data and multiple imputation, dwctaxon focuses on darwin core, taxonomy and data validation.
dwctaxon and rbmi 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 rbmi leans on clinical trials, missing data and multiple imputation, bundle focuses on serialization, tidymodels and model deployment.
bundle and rbmi 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 rbmi leans on clinical trials, missing data and multiple imputation, lime focuses on explainability, machine learning and maintenance mode.
lime and rbmi 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 rbmi?
The top rbmi alternatives we currently track in analytics tools are chattr, cloudml, tidymodels, datapack, USAboundaries, ranked by recent ship velocity.
How is this list of rbmi alternatives ranked?
Alternatives are ranked by Sparkpulse's velocity_score — release cadence + 30-day spark count + sector-relative ship rate.
Can I compare rbmi directly with one of these alternatives?
Yes — every card has a "Compare with rbmi" link to a side-by-side /compare page.