leaflet
leaflet relicensed to MIT and finished migrating off R's retired spatial stack
Comparison · Analytics
Countly vs readxl
A side-by-side editorial comparison of Countly and readxl — release velocity, themes, recent moves, and the top alternatives to consider.
Countly vs readxl: at a glance
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.
What is readxl?
readxl has shipped almost nothing but vendored-dependency upkeep since 2022.
readxl reads Excel files into R without requiring Excel, bundling the libxls and RapidXML C libraries. Four of its last six releases state outright that they contain no user-facing changes, existing instead to satisfy CRAN, silence a sanitizer warning, or re-embed a patched libxls.
Countly vs readxl: editorial side-by-side
Countly
5.0ANALYTICS
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.
readxl
0.0ANALYTICS
readxl has shipped almost nothing but vendored-dependency upkeep since 2022.
◆ Current state
readxl reads Excel files into R without requiring Excel, bundling the libxls and RapidXML C libraries. Four of its last six releases state outright that they contain no user-facing changes, existing instead to satisfy CRAN, silence a sanitizer warning, or re-embed a patched libxls.
◆ Where it's heading
The real work has become stewardship of vendored C code: absorbing libxls security fixes and keeping the package compiling across Alpine, UBSAN and successive cpp11 versions. 1.5.0 breaks the streak only slightly, with a network-drive permission warning fix and a cpp11 floor raised to dodge a segfault.
◆ Prediction
Expect the same rhythm — releases triggered by toolchain breakage or an upstream libxls patch rather than new spreadsheet-reading capability.
Alternatives to Countly and readxl
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 readxl.
ggpubr
ggpubr reached 1.0.0 with p-value formatting presets for specific journals
bigrquery
bigrquery went MIT, then handed its slowest path to the BigQuery Storage API
sparklyr
sparklyr now spends its releases absorbing dbplyr changes and feeding pysparklyr
Seurat
Seurat's centre of gravity has moved from single cells to spatial data and on-disk matrices
insight
insight quietly widens the set of model objects the easystats ecosystem can read
See all Countly alternatives → · See all readxl alternatives →
Recent activity from Countly and readxl
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoCountlyCustom-code sandbox swapped to isolated-vm; images rebuilt on Node 24
- 9d agoCountlyFixes for event keys containing special characters
- 9d agoCountlyJourney deeplinks take dynamic parameters; hooks validated on save
- 20d agoCountlyStar-rating logo path and data-manager transformation fixes
- 21d agoCountlyLTS backport: data-manager transformation fix
- 1mo agoCountlyJourneys survive user merges; SDK-provided asset paths
- 2mo agoreadxlreadxl 1.5.0 stops false access-denied warnings on network drives
- 1y agoreadxlreadxl 1.4.5 clears a gcc UBSAN warning
- 1y agoreadxlreadxl 1.4.4 embeds libxls 1.6.3 with vulnerability fixes
- 3y agoreadxlreadxl 1.4.3 ships with no user-facing changes
- 3y agoreadxlreadxl 1.4.2 embeds a libxls build fixing CVE-2021-27836
- 3y agoreadxlreadxl 1.4.1 regenerates help files for valid HTML5
Frequently asked questions
What is the difference between Countly and readxl?
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 readxl?
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 readxl?
Top readxl alternatives in Analytics are ranked by recent ship velocity. Browse the "readxl alternatives" section above for the current picks, or visit /alternatives/readxl for the full list with editorial commentary on each.