OpenHouse
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Comparison · Analytics
dplyr vs Fathom Analytics
A side-by-side editorial comparison of dplyr and Fathom Analytics — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:performance
dplyr vs Fathom Analytics: at a glance
What is dplyr?
After two quiet years dplyr widened its verb vocabulary in one release
dplyr sat on patch releases from late 2023 until 1.2.0 landed in February 2026, and that release did a lot at once: a filter_out() counterpart to filter(), elementwise when_any() and when_all(), and three new recoding verbs alongside case_when(). It also rewrote if_else(), case_when() and coalesce() in C via vctrs, and promoted .by and reframe() from experimental to stable. The follow-up 1.2.1 is a compliance patch.
What is Fathom Analytics?
Fathom rebuilds its query engine and bolts on Search Console, reaching for GA4's lunch.
Fathom shipped a complete analytics-engine rebuild in March 2026, paired with secondary dimensions, faster queries, and more accurate time-on-page measurement. The product is closing the feature gap with mainstream analytics tools while keeping its cookie-free, privacy-first stance. Recent additions — Google Search Console integration, entry/exit pages, dashboard ZIP exports, and a fresh layer of bot detection — directly target reasons users still keep GA4 open in another tab.
dplyr vs Fathom Analytics: editorial side-by-side
dplyr
0.0ANALYTICS
After two quiet years dplyr widened its verb vocabulary in one release
◆ Current state
dplyr sat on patch releases from late 2023 until 1.2.0 landed in February 2026, and that release did a lot at once: a filter_out() counterpart to filter(), elementwise when_any() and when_all(), and three new recoding verbs alongside case_when(). It also rewrote if_else(), case_when() and coalesce() in C via vctrs, and promoted .by and reframe() from experimental to stable. The follow-up 1.2.1 is a compliance patch.
◆ Where it's heading
The package is expanding its verb set deliberately, through published Tidyup design proposals rather than ad-hoc additions, and each new verb targets a case where the old idiom was error-prone - most obviously NA handling in negated filters. Underneath, hot paths keep moving from R into C, so the API grows while the runtime cost falls.
◆ Prediction
Expect the remaining experimental surface to follow .by and reframe() toward stable, and further hot paths to be rewritten in C via vctrs. The two Tidyup proposals referenced here suggest more of the filter and recode families is still being designed.
Fathom Analytics
1.3ANALYTICS
Fathom rebuilds its query engine and bolts on Search Console, reaching for GA4's lunch.
◆ Current state
Fathom shipped a complete analytics-engine rebuild in March 2026, paired with secondary dimensions, faster queries, and more accurate time-on-page measurement. The product is closing the feature gap with mainstream analytics tools while keeping its cookie-free, privacy-first stance. Recent additions — Google Search Console integration, entry/exit pages, dashboard ZIP exports, and a fresh layer of bot detection — directly target reasons users still keep GA4 open in another tab.
◆ Where it's heading
The roadmap is clearly aimed at making Fathom a viable single-pane replacement for Google Analytics rather than a privacy-first complement to it. Expect continued investment in detection accuracy, reporting depth (custom exports, secondary dimensions), and Google-side integrations. The new analytics engine is foundational — it is what makes the next layer of features possible.
◆ Prediction
Next likely moves are deeper UTM and campaign analytics, an experimentation or goals-funnel surface, and tighter agency tooling that builds on self-serve site transfer and shared-dashboard exports.
Alternatives to dplyr and Fathom 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 dplyr or Fathom Analytics.
silx
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
statsmodels
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
StatsBase.jl
StatsBase.jl is in caretaker mode — correctness fixes in, dependency bumps out.
iris
Iris ships steadily on a two-a-year cadence, but its feed publishes only pointers.
shiny
Shiny made reactive apps observable, then gave them a way to tear themselves down
See all dplyr alternatives → · See all Fathom Analytics alternatives →
Recent activity from dplyr and Fathom Analytics
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 4mo agoFathom AnalyticsA new layer of bot detection to keep your analytics accurate and free from non-human traffic
- 4mo agoFathom AnalyticsTrial signup landing page (not a changelog entry)
- 4mo agodplyrFull compliance with the R C API
- 5mo agoFathom AnalyticsSee where visitors land when they arrive at your site and where they leave from — right on your dashboard
- 5mo agoFathom AnalyticsWe rebuilt the analytics engine behind your Fathom dashboard from the ground up. ⚡
- 5mo agoFathom AnalyticsSee which search terms people use to find your site in search results, right inside your Fathom dashboard ⚡
- 5mo agoFathom AnalyticsUpdates and improvements to Fathom Analytics for February 2026
- 6mo agodplyrfilter_out(), when_any() and three recoding verbs land in 1.2.0 ⚡
- 2y agodplyrNamespaced join_by() helpers and refreshed bundled datasets
- 2y agodplyrDeprecation message and setequal() consistency fixes
- 3y agodplyrAll-NA join key fix and count() documentation
- 3y agodplyrJoins gain a relationship argument and warn far less often
Frequently asked questions
What is the difference between dplyr and Fathom Analytics?
Both compete on the same themes — performance — within Analytics. Fathom Analytics is currently shipping more aggressively (velocity 1.3 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 dplyr better than Fathom Analytics?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Fathom Analytics is currently shipping more aggressively (velocity 1.3 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 dplyr?
Top dplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "dplyr alternatives" section above for the current picks, or visit /alternatives/dplyr for the full list with editorial commentary on each.
What are the best alternatives to Fathom Analytics?
Top Fathom Analytics alternatives in Analytics are ranked by recent ship velocity. Browse the "Fathom Analytics alternatives" section above for the current picks, or visit /alternatives/fathom-analytics for the full list with editorial commentary on each.