mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
Comparison · Analytics
Countly vs textrecipes
A side-by-side editorial comparison of Countly and textrecipes — release velocity, themes, recent moves, and the top alternatives to consider.
Countly vs textrecipes: 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 textrecipes?
Text features finally stay sparse all the way to the model.
textrecipes supplies the recipes steps for turning text into model-ready columns: tokenizing, hashing, term frequency, TF-IDF, and word embeddings. Version 1.1.0 added a sparse argument to step_dummy_hash(), step_texthash(), step_tf() and step_tfidf() so they emit sparse vectors. The releases before it are a long consistency pass — keep_original_cols on every step that creates columns, informative errors on name collisions, tunable arguments documented, integer rather than double output where integers are what is meant.
Countly vs textrecipes: 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.
textrecipes
0.0ANALYTICS
Text features finally stay sparse all the way to the model.
◆ Current state
textrecipes supplies the recipes steps for turning text into model-ready columns: tokenizing, hashing, term frequency, TF-IDF, and word embeddings. Version 1.1.0 added a sparse argument to step_dummy_hash(), step_texthash(), step_tf() and step_tfidf() so they emit sparse vectors. The releases before it are a long consistency pass — keep_original_cols on every step that creates columns, informative errors on name collisions, tunable arguments documented, integer rather than double output where integers are what is meant.
◆ Where it's heading
Two forces drive this package. One is memory: text produces wide, mostly-zero matrices, and the sparse work is the direct answer, landing in the same period that workflows learned to fit and predict on dgCMatrix input. The other is upstream churn — the tweets tokenizer was deprecated because tokenizers deprecated it, the politeness feature disappeared when textfeatures left Suggests. The package's own agenda is consistency; its release timing belongs to its dependencies.
◆ Prediction
Expect the sparse argument to spread to the remaining column-producing steps, since only four of them have it, and expect more steps to be reworked as recipes' own sparse-data support matures.
Alternatives to Countly and textrecipes
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 textrecipes.
mlr3viz
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
mlr3tuning
mlr3tuning is rebuilding its async machinery under a stable public surface
timetk
timetk swallowed anomalize whole, then went quiet for two years
modelbased
modelbased is turning marginal effects into a full contrast grammar
parameters
easystats' parameters package absorbs one more model class every few weeks
See all Countly alternatives → · See all textrecipes alternatives →
Recent activity from Countly and textrecipes
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoCountlyCustom-code sandbox swapped to isolated-vm; images rebuilt on Node 24
- 10d agoCountlyFixes for event keys containing special characters
- 10d agoCountlyJourney deeplinks take dynamic parameters; hooks validated on save
- 20d agoCountlyStar-rating logo path and data-manager transformation fixes
- 22d agoCountlyLTS backport: data-manager transformation fix
- 1mo agoCountlyJourneys survive user merges; SDK-provided asset paths
- 1y agotextrecipesHashing and TF-IDF steps can emit sparse vectors ⚡
- 1y agotextrecipesstep_textfeatures() sped up; clean_levels NA bug fixed
- 2y agotextrecipestextfeatures dependency dropped; politeness feature removed
- 2y agotextrecipesuntokenize and normalization return factors
- 2y agotextrecipeskeep_original_cols everywhere; hashing column order fixed
- 3y agotextrecipesTunable arguments documented; name collisions now error
Frequently asked questions
What is the difference between Countly and textrecipes?
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 textrecipes?
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 textrecipes?
Top textrecipes alternatives in Analytics are ranked by recent ship velocity. Browse the "textrecipes alternatives" section above for the current picks, or visit /alternatives/textrecipes for the full list with editorial commentary on each.