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Countly vs pins

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

Countly vs pins: at a glance

FeatureCountlypins
SectorAnalyticsAnalytics
Velocity score5.00.0
Sparks · 30d00
Top themesproduct-analytics, self-hosted, security-hardening, sandboxingdata-versioning, cloud-storage, databricks, serialization
Last editorial update9h ago53m ago
WebsiteVisit →Visit →

What is Countly?

Countly's LTS line is spending its releases on hardening the surfaces customers extend.

The 25.03 LTS and 24.05 branches are moving together, and the recent content is dominated by security and scoping work rather than features. The latest LTS rebuilds the api and frontend Docker images as multi-stage builds on Debian 13 with Node 24 so compilers and build tooling no longer ship, overrides fourteen vulnerable transitive dependencies, and replaces the unmaintained v8-sandbox behind custom code with isolated-vm. Earlier releases scoped internal event hooks to their own apps, fixed the consents table returning fields beyond the consent columns, and stopped dashboard widgets being copied by users without access to the referenced apps.

Read the full Countly trajectory →

What is pins?

pins keeps adding a storage backend per release while retiring its original API

pins publishes and versions R objects to a board, where a board is whatever storage you have. The recent releases read as a steady list of new boards - Google Cloud Storage, Google Drive, Databricks Volumes, Connect vanity URLs - alongside serialization changes that track which formats R users actually want: parquet via nanoparquet, and qs replaced by qs2.

Read the full pins trajectory →

Countly vs pins: editorial side-by-side

C
Countly
ANALYTICS
5.0

Countly's LTS line is spending its releases on hardening the surfaces customers extend.

◆ Current state

The 25.03 LTS and 24.05 branches are moving together, and the recent content is dominated by security and scoping work rather than features. The latest LTS rebuilds the api and frontend Docker images as multi-stage builds on Debian 13 with Node 24 so compilers and build tooling no longer ship, overrides fourteen vulnerable transitive dependencies, and replaces the unmaintained v8-sandbox behind custom code with isolated-vm. Earlier releases scoped internal event hooks to their own apps, fixed the consents table returning fields beyond the consent columns, and stopped dashboard widgets being copied by users without access to the referenced apps.

◆ Where it's heading

The pattern across these releases is closing the gaps where a customer-supplied artefact — custom hook code, a copied widget, a projection on a request — could reach further than intended. That work is now touching the runtime itself, and the isolated-vm swap is a breaking change: custom code relying on setTimeout, setInterval or async completion fails with a logged error instead of running. The journey engine is the only place shipping genuinely new capability, and it is enterprise-only.

◆ Prediction

Expect follow-up releases to soften the custom-code migration, since the isolated-vm switch silently breaks any hook that awaited a timer, and further ab-testing work now that pystan has been replaced with compiled Stan executables.

P
pins
ANALYTICS
0.0

pins keeps adding a storage backend per release while retiring its original API

◆ Current state

pins publishes and versions R objects to a board, where a board is whatever storage you have. The recent releases read as a steady list of new boards - Google Cloud Storage, Google Drive, Databricks Volumes, Connect vanity URLs - alongside serialization changes that track which formats R users actually want: parquet via nanoparquet, and qs replaced by qs2.

◆ Where it's heading

Two long-running processes, neither dramatic. Backend coverage expands toward wherever teams already store artifacts, which increasingly means Databricks and cloud object storage rather than a shared drive. Meanwhile the legacy pin() API from before the board model has been in a staged deprecation across at least three releases, escalated each time rather than removed.

◆ Prediction

Expect another board or two as storage platforms are requested, and the legacy pin() functions to finally become errors; the format list will keep tracking whichever serializer the R community settles on.

Alternatives to Countly and pins

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 Countly or pins.

See all Countly alternatives → · See all pins alternatives →

Recent activity from Countly and pins

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

  1. 1d agoCountlyCustom-code sandbox swapped to isolated-vm; images rebuilt on Node 24
  2. 9d agoCountlyFixes for event keys containing special characters
  3. 9d agoCountlyJourney deeplinks take dynamic parameters; hooks validated on save
  4. 20d agoCountlyStar-rating logo path and data-manager transformation fixes
  5. 21d agoCountlyLTS backport: data-manager transformation fix
  6. 1mo agoCountlyJourneys survive user merges; SDK-provided asset paths
  7. 5mo agopinsqs2 replaces qs; pins can be written in multiple formats
  8. 1y agopinsPin previews on Connect; Databricks host normalization
  9. 1y agopinsAdds board_databricks() and switches parquet to nanoparquet
  10. 2y agopinspin_write() arguments must be named; Connect caches removed
  11. 2y agopinsMessage clarity and Google Drive dribble handling
  12. 2y agopinsboard_gdrive() added; cache location configurable

Frequently asked questions

What is the difference between Countly and pins?

They serve adjacent needs but don't currently overlap on shipped themes. Countly is currently shipping more aggressively (velocity 5.0 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 Countly better than pins?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Countly is currently shipping more aggressively (velocity 5.0 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 Countly?

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

What are the best alternatives to pins?

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