distributions3
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
A side-by-side editorial comparison of PostHog and tulpa — release velocity, themes, recent moves, and the top alternatives to consider.
PostHog is filling in Logs and the mobile SDKs while quietly growing a support product.
PostHog ships weekly, and this week's batch is spread across four teams rather than concentrated in one product. Logs gets attribute filtering and a React Native capture path; the iOS SDK gains rage-click detection and a session-replay duration floor; Conversations picks up GitHub issues as an inbound support channel. Individually these are small, and the weekly digest bundles them into a single roundup entry.
The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.
tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.
PostHog ships weekly, and this week's batch is spread across four teams rather than concentrated in one product. Logs gets attribute filtering and a React Native capture path; the iOS SDK gains rage-click detection and a session-replay duration floor; Conversations picks up GitHub issues as an inbound support channel. Individually these are small, and the weekly digest bundles them into a single roundup entry.
Two build-outs are running in parallel. The observability side — Logs plus the mobile SDKs — is being brought up to parity with what PostHog already offers on web, which is what makes the platform credible for mobile teams rather than web analytics with an SDK attached. The Conversations work is the more interesting thread: adding support channels moves PostHog past measuring users toward handling them, and it is being built out in the same incremental weekly rhythm as everything else.
Expect Logs and the mobile SDKs to keep receiving parity features on the weekly cadence, and expect Conversations to add further inbound channels beyond GitHub issues. The entries do not show whether Conversations is being positioned as a standalone product or a feature of the existing suite.
tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.
Two moves in nine days point at the same destination: the generics conversion made tulpa extensible by downstream packages, and CRAN admission makes it installable by them. The current cadence — several tags a week, some existing only to record a measurement that produced no code change — does not survive CRAN's submission overhead, so the release rhythm has to slow whether or not the project intends it. The correctness work still clusters on the joint nested-Laplace driver, and 0.1.0 extends the same diagnostics habit with .NL_AXIS_SD_REASONS, a closed vocabulary for an outer axis whose grid does not contain its own posterior mode.
Expect tulpaObs to follow tulpa onto CRAN, since it is the consumer whose registrations the engine has spent this window unblocking, and expect the version line to move in larger, less frequent steps now that each one carries a submission.
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 PostHog or tulpa.
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
Basedash keeps pushing its data out of the workspace — now to people without accounts
RStudio ships through release branches, and the notes are commit messages
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Fulcrum is betting its whole map stack on Esri, with a hard Google Maps cutoff on September 1.
Holistics keeps fencing in the AI layer it spent the summer building.
See all PostHog alternatives → · See all tulpa alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. tulpa is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. tulpa is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 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.
Top PostHog alternatives in Analytics are ranked by recent ship velocity. Browse the "PostHog alternatives" section above for the current picks, or visit /alternatives/posthog for the full list with editorial commentary on each.
Top tulpa alternatives in Analytics are ranked by recent ship velocity. Browse the "tulpa alternatives" section above for the current picks, or visit /alternatives/tulpa for the full list with editorial commentary on each.