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Comparison · Analytics
Neo4j vs probably
A side-by-side editorial comparison of Neo4j and probably — release velocity, themes, recent moves, and the top alternatives to consider.
Neo4j vs probably: at a glance
| Feature | Neo4j | probably |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 7.5 | 0.0 |
| Sparks · 30d | 2 | 0 |
| Top themes | graph-database, graph-data-science, free-tier, access-control | calibration, conformal-inference, tidymodels, uncertainty |
| Last editorial update | 18h ago | 50m ago |
| Website | — | Visit → |
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.
What is probably?
The package that made calibration a step instead of an afterthought.
probably started as a small utility for class predictions and equivocal zones, and version 1.0.0 turned it into tidymodels' calibration and uncertainty package: cal_plot_*, cal_estimate_*, cal_validate_* and cal_apply across binary, multiclass and regression problems, plus conformal prediction intervals. Since then the work has been consolidation — a large internal refactor with no API change, split conformal and conformal quantile regression, bound_prediction(), and required_pkgs() and butcher methods so conformal objects can be deployed and stripped.
Neo4j vs probably: editorial side-by-side
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.
probably
0.0ANALYTICS
The package that made calibration a step instead of an afterthought.
◆ Current state
probably started as a small utility for class predictions and equivocal zones, and version 1.0.0 turned it into tidymodels' calibration and uncertainty package: cal_plot_*, cal_estimate_*, cal_validate_* and cal_apply across binary, multiclass and regression problems, plus conformal prediction intervals. Since then the work has been consolidation — a large internal refactor with no API change, split conformal and conformal quantile regression, bound_prediction(), and required_pkgs() and butcher methods so conformal objects can be deployed and stripped.
◆ Where it's heading
The recent releases are about making these objects survive leaving the session. butcher and required_pkgs() methods are what a model needs to be pinned, containerised and served, and their arrival alongside workflows adding a tailor postprocessing stage and vetiver adding probably support points the same way: calibration is being moved out of analysis scripts and into the deployed pipeline. The cal_*_none() reference implementations are the tell that calibration is now something people tune rather than apply once.
◆ Prediction
Expect the calibration functions to be reachable directly from a tuned workflow's postprocessing stage rather than applied to predictions afterwards, following the tailor integration that workflows just shipped.
Alternatives to Neo4j and probably
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 Neo4j or probably.
textrecipes
Text features finally stay sparse all the way to the model.
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.
patchwork
patchwork stopped being a ggplot composer and became a page composer.
See all Neo4j alternatives → · See all probably alternatives →
Recent activity from Neo4j and probably
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 ⚡
- 10mo agoprobablyConformal objects gain required_pkgs() and butcher methods
- 1y agoprobablyggplot2 test updates and a clearer validation-set error
- 1y agoprobablyCalibration internals refactored; isotonic bootstrap bug fixed
- 2y agoprobablyFix grouping sensitivity to variable type
- 3y agoprobablySplit conformal and conformal quantile regression added
- 3y agoprobablyCalibration and conformal inference arrive in tidymodels ⚡
Frequently asked questions
What is the difference between Neo4j and probably?
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 Neo4j better than probably?
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 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.
What are the best alternatives to probably?
Top probably alternatives in Analytics are ranked by recent ship velocity. Browse the "probably alternatives" section above for the current picks, or visit /alternatives/probably for the full list with editorial commentary on each.