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Appfigures vs Deequ

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

Appfigures vs Deequ: at a glance

FeatureAppfiguresDeequ
SectorAnalyticsAnalytics
Velocity score3.80.0
Sparks · 30d10
Top themesapp-analytics, agentic, aso, competitive-intelligencedata-quality, spark, dqdl, jvm-library
Last editorial update10h ago2h ago
WebsiteVisit →

What is Appfigures?

Appfigures just made its app-market data something an AI agent can query, not something you screenshot.

Appfigures has spent the last year widening what its estimates cover — iPad data folded into every download and revenue figure, state-level financials in the API, a 15-report App Intelligence suite for competitor research, and Leaderboards that rank apps by explicit metrics instead of opaque store charts. The August release changes who consumes all of that: a CLI built specifically for AI agents, with a hinting system to keep them from misreading the data. The product is no longer only a dashboard.

Read the full Appfigures 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 →

Appfigures vs Deequ: editorial side-by-side

A
Appfigures
ANALYTICS
3.8

Appfigures just made its app-market data something an AI agent can query, not something you screenshot.

◆ Current state

Appfigures has spent the last year widening what its estimates cover — iPad data folded into every download and revenue figure, state-level financials in the API, a 15-report App Intelligence suite for competitor research, and Leaderboards that rank apps by explicit metrics instead of opaque store charts. The August release changes who consumes all of that: a CLI built specifically for AI agents, with a hinting system to keep them from misreading the data. The product is no longer only a dashboard.

◆ Where it's heading

The arc runs from data completeness to data access. First they closed gaps in the underlying estimates, then they built more ways to slice them, and now they are exposing the whole surface to agents that can investigate, compare, monitor, and act — including replying to reviews and adjusting Apple Ads campaigns. Each layer assumes the one below it is trustworthy, which is why the accuracy fixes (iPad coverage, keyword popularity, Google Play delay removal) came first.

◆ Prediction

Expect the agent surface to deepen before it widens — more write actions exposed through the CLI, and Leaderboards and App Intelligence reports made directly queryable by agents rather than only through the web reports.

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 Appfigures 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 Appfigures or Deequ.

See all Appfigures alternatives → · See all Deequ alternatives →

Recent activity from Appfigures and Deequ

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

  1. 11h agoAppfiguresIntroducing the Appfigures CLI
  2. 1mo agoAppfiguresIntroducing Appfigures Leaderboards
  3. 3mo agoDeequDeequ adds a processRowsTyped API for typed outcome access
  4. 3mo agoDeequDeequ 3.0.1 fixes the publish workflow branch
  5. 3mo agoDeequDeequ 3.0.0 adds a Range analyzer with DQDL rule support
  6. 3mo agoAppfiguresApp Intelligence for iPad
  7. 4mo agoDeequDeequ 2.0.15 tag carries only a pom version bump
  8. 8mo agoAppfiguresSupport for By State Financial Reports via the API
  9. 8mo agoAppfiguresDaily Averages Across Reports
  10. 8mo agoAppfiguresIntroducing the New App Intelligence

Frequently asked questions

What is the difference between Appfigures and Deequ?

They serve adjacent needs but don't currently overlap on shipped themes. Appfigures is currently shipping more aggressively (velocity 3.8 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 Appfigures better than Deequ?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Appfigures is currently shipping more aggressively (velocity 3.8 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 Appfigures?

Top Appfigures alternatives in Analytics are ranked by recent ship velocity. Browse the "Appfigures alternatives" section above for the current picks, or visit /alternatives/appfigures 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.