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Comparison · Analytics
Deequ vs Pirsch Analytics
A side-by-side editorial comparison of Deequ and Pirsch Analytics — release velocity, themes, recent moves, and the top alternatives to consider.
Deequ vs Pirsch Analytics: at a glance
| Feature | Deequ | Pirsch Analytics |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 0.0 | 3.8 |
| Sparks · 30d | 0 | 0 |
| Top themes | data-quality, spark, dqdl, jvm-library | privacy analytics, bot filtering, maintenance, dashboards |
| Last editorial update | 11h ago | 3mo ago |
| Website | Visit → | — |
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.
What is Pirsch Analytics?
Pirsch ships a tight maintenance cadence — bot filtering, dashboard polish, and dependency hygiene.
Pirsch is releasing every few days with very small payloads. The April cluster centers on bot detection — improved filters in 2.14.10 and 2.14.12, plus a referrer-parameter bot fix in 2.14.11. March added dashboard creation settings, an option to hide the UTM panel, expiration times on access links, and a referrer blacklist update. Earlier in February, email reports gained a start date and the Fathom Analytics importer was updated.
Deequ vs Pirsch Analytics: editorial side-by-side
Deequ
0.0ANALYTICS
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.
Pirsch Analytics
3.8ANALYTICS
Pirsch ships a tight maintenance cadence — bot filtering, dashboard polish, and dependency hygiene.
◆ Current state
Pirsch is releasing every few days with very small payloads. The April cluster centers on bot detection — improved filters in 2.14.10 and 2.14.12, plus a referrer-parameter bot fix in 2.14.11. March added dashboard creation settings, an option to hide the UTM panel, expiration times on access links, and a referrer blacklist update. Earlier in February, email reports gained a start date and the Fathom Analytics importer was updated.
◆ Where it's heading
Pirsch is in steady operational mode — defending against bots, polishing dashboard surfaces, and keeping dependencies current. The Fathom importer updates and email-report work are the only signs of growth-oriented investment; otherwise the cadence is custodial. The product feels like it's competing on reliability and privacy rather than feature surface.
◆ Prediction
Expect bot-filter work to continue (this is an arms race for any analytics provider) and the Fathom importer to keep getting attention as Fathom users churn. Larger directional moves aren't visible in the feed; the next signal would be a real new product surface — funnels v2, server-side eventing, or an AI insights panel.
Alternatives to Deequ and Pirsch Analytics
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 Deequ or Pirsch Analytics.
Omni
Omni ships weekly, and almost every week the headline item is an AI feature
OpenDataDiscovery
Four ODD Platform releases in two weeks, and not one of them changes the product
Apache Baremaps
Baremaps got geoparquet and hillshading, then went quiet for eighteen months in incubation
Marquez
Marquez spent 2024 turning a lineage store into a UI, then stopped releasing
Amundsen
Amundsen's last release was a config flag, and the feed has been silent for two years
See all Deequ alternatives → · See all Pirsch Analytics alternatives →
Recent activity from Deequ and Pirsch Analytics
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agoDeequDeequ adds a processRowsTyped API for typed outcome access
- 3mo agoPirsch Analyticsv2.14.12: improved bot filters
- 3mo agoDeequDeequ 3.0.1 fixes the publish workflow branch
- 3mo agoDeequDeequ 3.0.0 adds a Range analyzer with DQDL rule support
- 3mo agoPirsch Analyticsv2.14.11: fix bot filtering by referrer parameter
- 3mo agoPirsch Analyticsv2.14.10: bot filter improvements and graph fix
- 4mo agoDeequDeequ 2.0.15 tag carries only a pom version bump
- 5mo agoPirsch Analyticsv2.14.9: referrer blacklist update
- 5mo agoPirsch Analyticsv2.14.8: fix account deletion with pinned dashboards
- 5mo agoPirsch Analyticsv2.14.7: dashboard settings, UTM panel toggle, link expiration
Frequently asked questions
What is the difference between Deequ and Pirsch Analytics?
They serve adjacent needs but don't currently overlap on shipped themes. Pirsch Analytics is currently shipping more aggressively (velocity 3.8 vs 0.0), with 0 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 Deequ better than Pirsch Analytics?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Pirsch Analytics is currently shipping more aggressively (velocity 3.8 vs 0.0), with 0 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 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.
What are the best alternatives to Pirsch Analytics?
Top Pirsch Analytics alternatives in Analytics are ranked by recent ship velocity. Browse the "Pirsch Analytics alternatives" section above for the current picks, or visit /alternatives/pirsch for the full list with editorial commentary on each.