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Apache Druid vs distributions3

A side-by-side editorial comparison of Apache Druid and distributions3 — release velocity, themes, recent moves, and the top alternatives to consider.

Apache Druid vs distributions3: at a glance

FeatureApache Druiddistributions3
SectorAnalytics, Infra & APIsAnalytics
Velocity score0.06.3
Sparks · 30d01
Top themesreal-time-analytics, apache-project, quarterly-releases, upgrade-compatibilityr-package, probability-distributions, empirical-distributions, likelihood-inference
Last editorial update23d ago5h ago
WebsiteVisit →Visit →

What is Apache Druid?

Druid ships a large major roughly every quarter and lets the release notes do the talking.

The feed alternates release-candidate tags with the majors they become: 35.0.1 in December, 36.0.0 in February, 37.0.0 in May. The majors are big and diffuse — 37.0.0 counts over 255 changes from 29 contributors, 36.0.0 over 189 from 34 — and are summarised by contributor counts and pointers to upgrade notes rather than headline features. The one patch in the window fixed segment-drop file descriptors leaking until process exit, which is the kind of detail that tells you who runs this: operators with long-lived clusters.

Read the full Apache Druid trajectory →

What is distributions3?

distributions3 0.3.0 adds sample-based distributions and likelihood derivatives

An R package giving probability distributions a consistent object interface - d/p/q/r functions, moments, and prodist() methods that pull a fitted distribution out of a regression object. Version 0.3.0 is the first substantive release under Achim Zeileis's maintenance, and it widens what a distribution is allowed to be: Empirical() represents a distribution by a random sample rather than by parameters, and numerical fallbacks now fill in cdf(), pdf(), quantile(), random() and the moments for any object that implements only some of them. New score() and hessian() generics compute first and second derivatives of the log-likelihood with respect to the parameters, analytically for a few distributions and numerically for the rest.

Read the full distributions3 trajectory →

Apache Druid vs distributions3: editorial side-by-side

Apache Druid logo
Apache Druid
ANALYTICSINFRA · APIS
0.0

Druid ships a large major roughly every quarter and lets the release notes do the talking.

◆ Current state

The feed alternates release-candidate tags with the majors they become: 35.0.1 in December, 36.0.0 in February, 37.0.0 in May. The majors are big and diffuse — 37.0.0 counts over 255 changes from 29 contributors, 36.0.0 over 189 from 34 — and are summarised by contributor counts and pointers to upgrade notes rather than headline features. The one patch in the window fixed segment-drop file descriptors leaking until process exit, which is the kind of detail that tells you who runs this: operators with long-lived clusters.

◆ Where it's heading

This is a mature Apache project on a predictable cadence, where each release aggregates hundreds of contributions instead of pursuing a theme. Every major carries explicit incompatible-changes and upgrade notes, so compatibility management is treated as a first-class part of shipping. Nothing in the feed points toward a directional shift; the signal is steadiness.

◆ Prediction

On this cadence the next major and its release candidate are due within a quarter of 37.0.0, likely with a similar volume of changes. What those changes contain cannot be inferred — the entries deliberately defer detail to the linked notes.

D6.3

distributions3 0.3.0 adds sample-based distributions and likelihood derivatives

◆ Current state

An R package giving probability distributions a consistent object interface - d/p/q/r functions, moments, and prodist() methods that pull a fitted distribution out of a regression object. Version 0.3.0 is the first substantive release under Achim Zeileis's maintenance, and it widens what a distribution is allowed to be: Empirical() represents a distribution by a random sample rather than by parameters, and numerical fallbacks now fill in cdf(), pdf(), quantile(), random() and the moments for any object that implements only some of them. New score() and hessian() generics compute first and second derivatives of the log-likelihood with respect to the parameters, analytically for a few distributions and numerically for the rest.

◆ Where it's heading

Growth used to arrive as new distribution families contributed from outside - the extreme-value set, Erlang, later the Poisson binomial. This release changes the axis: alongside two new distributions it adds an inference layer (score, hessian) and a forecast-evaluation one (crps() methods against scoringRules), which are capabilities about distributions rather than more of them. Dependency weight is being cut at the same time, with ggplot2 demoted to Suggests and glue replaced by base R sprintf().

◆ Prediction

With numeric fallbacks and the derivative generics in place, expect analytic score() and hessian() methods to be filled in across more of the distribution catalogue. The constructor-default change is the likeliest source of follow-up fixes, since calls like Poisson() now return a length-zero distribution where they previously errored.

Alternatives to Apache Druid and distributions3

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 Apache Druid or distributions3.

See all Apache Druid alternatives → · See all distributions3 alternatives →

Recent activity from Apache Druid and distributions3

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 6h agodistributions3Empirical distributions, plus score and hessian generics
  2. 29d agodistributions3Maintenance moves to Achim Zeileis; moment calculations corrected
  3. 3mo agoApache DruidDruid 37.0.0
  4. 4mo agoApache Druiddruid-37.0.0-rc1
  5. 6mo agoApache DruidDruid 36.0.0
  6. 6mo agoApache Druiddruid-36.0.0-rc1
  7. 8mo agoApache DruidDruid 35.0.1
  8. 8mo agoApache Druiddruid-35.0.1-rc2
  9. 10mo agodistributions3ggplot2 compatibility for the plotting functions
  10. 1y agodistributions3Poisson binomial distribution, with a normal-approximation fallback
  11. 3y agodistributions3is_discrete and is_continuous generics, plus elementwise type-safety
  12. 4y agodistributions3Extreme-value family, Erlang, and a plotting generic

Frequently asked questions

What is the difference between Apache Druid and distributions3?

They serve adjacent needs but don't currently overlap on shipped themes. distributions3 is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 Apache Druid better than distributions3?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributions3 is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 Apache Druid?

Top Apache Druid alternatives in Analytics are ranked by recent ship velocity. Browse the "Apache Druid alternatives" section above for the current picks, or visit /alternatives/apache-druid for the full list with editorial commentary on each.

What are the best alternatives to distributions3?

Top distributions3 alternatives in Analytics are ranked by recent ship velocity. Browse the "distributions3 alternatives" section above for the current picks, or visit /alternatives/distributions3-r for the full list with editorial commentary on each.