ANALYTICS
mlr3mbo picked its defaults from a benchmark study, not from taste
Alternatives · analytics tools
ggraph alternatives
The best ggraph alternatives in analytics tools, ranked by Sparkpulse's velocity_score.
Updated Aug 13, 2026
Looking for the best alternatives to ggraph? Sparkpulse tracks and ranks 12 alternatives in analytics tools by shipping velocity — how frequently each ships meaningful updates, verified from official changelogs. For reference, ggraph 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 ggraph
ggraph has settled into ggplot2 compatibility duty
ggraph provides the grammar of graphics for network and tree data. Its recent releases are compatibility and bug-fix work — a collapse fix in get_edges() alongside ggplot2 v4.0.0 upkeep, and before that a pipe rollback. The last release with real content was 2.2.0, a long list of layout and edge-geom corrections.
Velocity 0.0 · Last update 1h ago
Top 12 alternatives to ggraph
Ranked by recent ship velocity. Tap any card for the full editorial breakdown, or pivot to a head-to-head.
ANALYTICS
loo keeps rewriting the diagnostics Bayesian modellers read off model comparison
ANALYTICS
comtradr's 1.0 line is a long tail of patches against a brittle UN trade API.
ANALYTICS
bbotk is generalizing from an optimizer toolkit into an evaluation framework.
ANALYTICS
patchwork stopped being a ggplot composer and became a page composer.
ANALYTICS
mlr3fselect turned feature selection into an asynchronous, distributable job
ANALYTICS
lime survives on compatibility patches years after its research moment
ANALYTICS
mlr3measures is systematically retrofitting sample weights across every metric
ANALYTICS
mlr3cluster went from a handful of clusterers to covering the field
ANALYTICS
mlr3filters grows one feature-selection filter at a time
ANALYTICS
mlr3learners spends its releases absorbing upstream churn
ANALYTICS
gutenbergr has been rebuilt around caching and mirror resilience
ggraph 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 |
|---|---|---|---|---|
| ggraph (baseline) | 0.0 | 0 | network-visualizationggplot2r-stats | — |
| mlr3mbo | 2.5 | 0 | bayesian-optimizationmlr3hyperparameter-tuning | mlr3mbo 1.0.0 ships benchmark-derived default settings |
| loo | 2.5 | 0 | bayesiancross-validationstan | loo_compare returns a data.frame with new uncertainty columns |
| comtradr | 2.5 | 0 | trade dataapi wrapperun comtrade | — |
| bbotk | 2.5 | 0 | black-box optimizationmlr3async execution | EvalInstance base class separates evaluation from optimization |
| patchwork | 0.0 | 0 | ggplot2compositiontables | gt tables become first-class patchwork objects |
| mlr3fselect | 0.0 | 0 | feature-selectionmlr3machine-learning | Asynchronous feature selection arrives with FSelectorAsync |
| lime | 0.0 | 0 | interpretabilitymachine-learningr-stats | — |
| mlr3measures | 0.0 | 0 | metricsmlr3machine-learning | — |
| mlr3cluster | 0.0 | 0 | clusteringmlr3machine-learning | Nine new clustering learners in one release |
| mlr3filters | 0.0 | 0 | feature-selectionmlr3machine-learning | — |
| mlr3learners | 0.0 | 0 | mlr3machine-learningr-stats | — |
| gutenbergr | 0.0 | 0 | text-miningr-statscaching | — |
The 12 best ggraph alternatives, in depth
1. mlr3mbo · velocity 2.5
Mlr3mbo picked its defaults from a benchmark study, not from taste.
Its velocity score of 2.5/10 reflects longer-term release cadence; its most recent meaningful update was “mlr3mbo 1.0.0 ships benchmark-derived default settings”.
Where ggraph leans on network visualization, ggplot2 and r stats, mlr3mbo focuses on bayesian optimization, mlr3 and hyperparameter tuning.
mlr3mbo and ggraph have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
2. loo · velocity 2.5
Loo keeps rewriting the diagnostics Bayesian modellers read off model comparison.
Its velocity score of 2.5/10 reflects longer-term release cadence; its most recent meaningful update was “loo_compare returns a data.frame with new uncertainty columns”.
Where ggraph leans on network visualization, ggplot2 and r stats, loo focuses on bayesian, cross validation and stan.
loo and ggraph have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
3. comtradr · velocity 2.5
Comtradr's 1.0 line is a long tail of patches against a brittle UN trade API.
Its velocity score of 2.5/10 reflects longer-term release cadence.
Where ggraph leans on network visualization, ggplot2 and r stats, comtradr focuses on trade data, api wrapper and un comtrade.
comtradr and ggraph have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
4. bbotk · velocity 2.5
Bbotk is generalizing from an optimizer toolkit into an evaluation framework.
Its velocity score of 2.5/10 reflects longer-term release cadence; its most recent meaningful update was “EvalInstance base class separates evaluation from optimization”.
Where ggraph leans on network visualization, ggplot2 and r stats, bbotk focuses on black box optimization, mlr3 and async execution.
bbotk and ggraph have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
5. patchwork · velocity 0.0
Patchwork stopped being a ggplot composer and became a page composer.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “gt tables become first-class patchwork objects”.
Where ggraph leans on network visualization, ggplot2 and r stats, patchwork focuses on ggplot2, composition and tables.
patchwork and ggraph have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
6. mlr3fselect · velocity 0.0
Mlr3fselect turned feature selection into an asynchronous, distributable job.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Asynchronous feature selection arrives with FSelectorAsync”.
Where ggraph leans on network visualization, ggplot2 and r stats, mlr3fselect focuses on feature selection, mlr3 and machine learning.
mlr3fselect and ggraph have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full mlr3fselect trajectory → · Compare ggraph vs mlr3fselect →
7. lime · velocity 0.0
Lime survives on compatibility patches years after its research moment.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where ggraph leans on network visualization, ggplot2 and r stats, lime focuses on interpretability, machine learning and r stats.
lime and ggraph have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
8. mlr3measures · velocity 0.0
Mlr3measures is systematically retrofitting sample weights across every metric.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where ggraph leans on network visualization, ggplot2 and r stats, mlr3measures focuses on metrics, mlr3 and machine learning.
mlr3measures and ggraph have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full mlr3measures trajectory → · Compare ggraph vs mlr3measures →
9. mlr3cluster · velocity 0.0
Mlr3cluster went from a handful of clusterers to covering the field.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Nine new clustering learners in one release”.
Where ggraph leans on network visualization, ggplot2 and r stats, mlr3cluster focuses on clustering, mlr3 and machine learning.
mlr3cluster and ggraph have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full mlr3cluster trajectory → · Compare ggraph vs mlr3cluster →
10. mlr3filters · velocity 0.0
Mlr3filters grows one feature-selection filter at a time.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where ggraph leans on network visualization, ggplot2 and r stats, mlr3filters focuses on feature selection, mlr3 and machine learning.
mlr3filters and ggraph have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full mlr3filters trajectory → · Compare ggraph vs mlr3filters →
11. mlr3learners · velocity 0.0
Mlr3learners spends its releases absorbing upstream churn.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where ggraph leans on network visualization, ggplot2 and r stats, mlr3learners focuses on mlr3, machine learning and r stats.
mlr3learners and ggraph have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full mlr3learners trajectory → · Compare ggraph vs mlr3learners →
12. gutenbergr · velocity 0.0
Gutenbergr has been rebuilt around caching and mirror resilience.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where ggraph leans on network visualization, ggplot2 and r stats, gutenbergr focuses on text mining, r stats and caching.
gutenbergr and ggraph have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full gutenbergr trajectory → · Compare ggraph vs gutenbergr →
Frequently asked questions
What are the best alternatives to ggraph?
The top ggraph alternatives we currently track in analytics tools are mlr3mbo, loo, comtradr, bbotk, patchwork, ranked by recent ship velocity.
How is this list of ggraph alternatives ranked?
Alternatives are ranked by Sparkpulse's velocity_score — release cadence + 30-day spark count + sector-relative ship rate.
Can I compare ggraph directly with one of these alternatives?
Yes — every card has a "Compare with ggraph" link to a side-by-side /compare page.