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Comparison · Analytics
mlr3measures vs Neo4j
A side-by-side editorial comparison of mlr3measures and Neo4j — release velocity, themes, recent moves, and the top alternatives to consider.
mlr3measures vs Neo4j: at a glance
| Feature | mlr3measures | Neo4j |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 0.0 | 7.5 |
| Sparks · 30d | 0 | 2 |
| Top themes | metrics, mlr3, machine-learning, r-stats | graph-database, graph-data-science, free-tier, access-control |
| Last editorial update | 1h ago | 18h ago |
| Website | Visit → | — |
What is mlr3measures?
mlr3measures is systematically retrofitting sample weights across every metric
mlr3measures is the metric library behind mlr3. Recent releases follow two threads: adding measures — linex, pinball, Mu AUC, gmean, gpr, mcc — and retrofitting sample_weights support across the existing ones, reaching AUC and the confusion-matrix family in 1.3.0. Along the way 1.1.0 deprecated four regression measures and corrected the bias definitions.
What is Neo4j?
Neo4j moves its full graph algorithm catalog onto the free tier and adds attribute-based access control.
Neo4j is pushing capability downward and outward at the same time. The complete Graph Data Science catalog — 65+ algorithms — now runs on AuraDB Free in isolated, unbilled sessions, while Business Critical and Virtual Dedicated Cloud tiers gain attribute-based access control with time-windowed permissions and IdP claim mapping. Around those, the Aura platform continues its monthly cadence: Cypher 25 picked up GROUP BY and a GQL cardinality function, quantized vector search reached general availability, and the Query editor gained persistent tabs.
mlr3measures vs Neo4j: editorial side-by-side
mlr3measures
0.0ANALYTICS
mlr3measures is systematically retrofitting sample weights across every metric
◆ Current state
mlr3measures is the metric library behind mlr3. Recent releases follow two threads: adding measures — linex, pinball, Mu AUC, gmean, gpr, mcc — and retrofitting sample_weights support across the existing ones, reaching AUC and the confusion-matrix family in 1.3.0. Along the way 1.1.0 deprecated four regression measures and corrected the bias definitions.
◆ Where it's heading
The library is maturing rather than growing: weighted evaluation and observation-wise loss functions are being brought to metrics that already existed, which is what downstream weighted-resampling and per-observation analysis need. The deprecations suggest the maintainers are willing to remove measures they consider ill-defined rather than keep them for compatibility.
◆ Prediction
Expect sample_weights and observation-wise variants to reach the remaining measures that lack them.
Neo4j
7.5ANALYTICS
Neo4j moves its full graph algorithm catalog onto the free tier and adds attribute-based access control.
◆ Current state
Neo4j is pushing capability downward and outward at the same time. The complete Graph Data Science catalog — 65+ algorithms — now runs on AuraDB Free in isolated, unbilled sessions, while Business Critical and Virtual Dedicated Cloud tiers gain attribute-based access control with time-windowed permissions and IdP claim mapping. Around those, the Aura platform continues its monthly cadence: Cypher 25 picked up GROUP BY and a GQL cardinality function, quantized vector search reached general availability, and the Query editor gained persistent tabs.
◆ Where it's heading
The shape here is a funnel. Free-tier users get the algorithm catalog and hosted MCP access with no billing and no setup, which lowers the cost of the first serious graph experiment to nothing; enterprise tiers get the governance controls that make an expansion defensible. Cypher is simultaneously being pulled toward the GQL standard and extended with new surfaces — auth rules, grouping clauses — so the query language is absorbing work that used to sit in configuration and driver code.
◆ Prediction
Expect ABAC to descend to Professional tiers and the Aura Graph Analytics free session limits to become the pressure point Neo4j uses to convert experiments into paid capacity. The unresolved question from these entries is whether MCP for Aura reaches Virtual Dedicated Cloud, which is listed as pending.
Alternatives to mlr3measures and Neo4j
Other Analytics 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 mlr3measures or Neo4j.
textrecipes
Text features finally stay sparse all the way to the model.
probably
The package that made calibration a step instead of an afterthought.
workflowsets
workflowsets keeps widening what counts as a model worth comparing.
workflows
The tidymodels pipeline grew a third stage, and it happens after the model runs.
vetiver
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
See all mlr3measures alternatives → · See all Neo4j alternatives →
Recent activity from mlr3measures and Neo4j
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoNeo4jAura Graph Analytics is now available on AuraDB Free ⚡
- 1d agoNeo4jDynamic & Time-Based Access Control with ABAC, now in Neo4j Aura!
- 8d agoNeo4jQuery Tabs: A new way to work with your queries
- 9d agoNeo4jCypher 25 gains GROUP BY; quantized vector search hits GA
- 13d agoNeo4jEnterprise Studio: dashboard parameters and concurrent editing
- 22d agoNeo4jMCP for Aura Now Available ⚡
- 3mo agomlr3measuresWeighted AUC and weighted confusion-matrix measures
- 8mo agomlr3measuresObservation-wise loss for bbrier and logloss
- 11mo agomlr3measuresrse, rsq, rrse and rae deprecated; bias measures corrected
- 1y agomlr3measureslinex, pinball and Mu AUC measures added
- 2y agomlr3measuresgmean, gpr and multiclass MCC added
- 4y agomlr3measuresObservation-wise loss functions introduced
Frequently asked questions
What is the difference between mlr3measures and Neo4j?
They serve adjacent needs but don't currently overlap on shipped themes. Neo4j is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 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 mlr3measures better than Neo4j?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Neo4j is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to mlr3measures?
Top mlr3measures alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3measures alternatives" section above for the current picks, or visit /alternatives/mlr3measures for the full list with editorial commentary on each.
What are the best alternatives to Neo4j?
Top Neo4j alternatives in Analytics are ranked by recent ship velocity. Browse the "Neo4j alternatives" section above for the current picks, or visit /alternatives/neo4j for the full list with editorial commentary on each.