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Apache Druid vs Deequ

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

Apache Druid vs Deequ: at a glance

FeatureApache DruidDeequ
SectorAnalytics, Infra & APIsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesreal-time-analytics, apache-project, quarterly-releases, upgrade-compatibilitydata-quality, spark, dqdl, jvm-library
Last editorial update14d ago13h 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 Deequ?

Deequ ships GitHub tags whose release notes are one commit message long

Deequ is a data quality library for Spark, and it releases per Spark version — tags carry a -spark-3.5 or -spark-4.0 suffix, so the same code line ships more than once. The release notes are whatever the last commit message said, which here means each entry is a single line. Four releases landed in a month between March and April 2026, and only two of them contain any product change: a Range analyzer with DQDL rule support, and a processRowsTyped API for typed outcome access.

Read the full Deequ trajectory →

Apache Druid vs Deequ: 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.

D
Deequ
ANALYTICS
0.0

Deequ ships GitHub tags whose release notes are one commit message long

◆ Current state

Deequ is a data quality library for Spark, and it releases per Spark version — tags carry a -spark-3.5 or -spark-4.0 suffix, so the same code line ships more than once. The release notes are whatever the last commit message said, which here means each entry is a single line. Four releases landed in a month between March and April 2026, and only two of them contain any product change: a Range analyzer with DQDL rule support, and a processRowsTyped API for typed outcome access.

◆ Where it's heading

The visible work points in one direction — making check results programmatically consumable rather than just readable. A typed outcome API and a rule language binding are what you build when Deequ is being called from a pipeline that reacts to the result, not from a notebook where a human reads it. The column-pruning override added alongside the Range analyzer suggests the same attention on the cost side, keeping analyzers from scanning columns they do not reference.

◆ Prediction

The entries are too thin to support a confident read of what comes next; the only clear pattern is that each change will ship separately against Spark 3.5 and Spark 4.0, so the version skew between those branches will keep widening.

Alternatives to Apache Druid and Deequ

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 Deequ.

See all Apache Druid alternatives → · See all Deequ alternatives →

Recent activity from Apache Druid and Deequ

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

  1. 3mo agoApache DruidDruid 37.0.0
  2. 3mo agoDeequDeequ adds a processRowsTyped API for typed outcome access
  3. 3mo agoDeequDeequ 3.0.1 fixes the publish workflow branch
  4. 3mo agoDeequDeequ 3.0.0 adds a Range analyzer with DQDL rule support
  5. 3mo agoApache Druiddruid-37.0.0-rc1
  6. 4mo agoDeequDeequ 2.0.15 tag carries only a pom version bump
  7. 6mo agoApache DruidDruid 36.0.0
  8. 6mo agoApache Druiddruid-36.0.0-rc1
  9. 7mo agoApache DruidDruid 35.0.1
  10. 8mo agoApache Druiddruid-35.0.1-rc2

Frequently asked questions

What is the difference between Apache Druid and Deequ?

They serve adjacent needs but don't currently overlap on shipped themes. Apache Druid and Deequ are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). 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 Deequ?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Apache Druid and Deequ are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). 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 Deequ?

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