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Basedash vs fmtr

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

Basedash vs fmtr: at a glance

FeatureBasedashfmtr
SectorAnalyticsAnalytics
Velocity score7.50.0
Sparks · 30d10
Top themesbi, ai-analyst, external-sharing, apisas-parity, data-formatting, clinical-reporting, format-catalogues
Last editorial update1h ago3d ago
WebsiteVisit →Visit →

What is Basedash?

Basedash keeps pushing its data out of the workspace — now to people without accounts

Basedash is a BI tool built around an AI data analyst, and the last month has been about getting its output to more places: an API that exposes chat, insights, automations and dashboards; scheduled snapshots to email and Slack; and now a link that opens a live, filterable dashboard for someone with no Basedash account. Alongside that distribution work sits a research-preview agent, Tasks, that reads company data and produces a ranked to-do list. Audit logs, including a record of every query the AI runs, arrived in the same window.

Read the full Basedash trajectory →

What is fmtr?

Rebuilding SAS's formatting layer in R, one format specification at a time

fmtr applies formats to R data the way SAS applies them: named format catalogues, format lists, and an fapply() that maps a specification onto a vector. It is part of a family of packages that reconstruct SAS reporting idioms in R, and it shares infrastructure with them — labels.data.frame() was moved out to the common package, which fmtr now depends on. The recent releases have been closing specific gaps against SAS's own format vocabulary.

Read the full fmtr trajectory →

Basedash vs fmtr: editorial side-by-side

B
Basedash
ANALYTICS
7.5

Basedash keeps pushing its data out of the workspace — now to people without accounts

◆ Current state

Basedash is a BI tool built around an AI data analyst, and the last month has been about getting its output to more places: an API that exposes chat, insights, automations and dashboards; scheduled snapshots to email and Slack; and now a link that opens a live, filterable dashboard for someone with no Basedash account. Alongside that distribution work sits a research-preview agent, Tasks, that reads company data and produces a ranked to-do list. Audit logs, including a record of every query the AI runs, arrived in the same window.

◆ Where it's heading

Two arcs are running in parallel. One narrows the gap between viewing data and acting on it — suggestions before you type a prompt, then Tasks writing the work item and tracking whether the metric moved. The other decouples consumption from seats: API, subscriptions, and public links each reach an audience that never logs in. The interface work (module-anchored sidebar, per-user table sorting that doesn't rewrite the author's SQL) reads as load-bearing for both.

◆ Prediction

Tasks leaving research preview is the release that decides how much of this is real; its value depends entirely on the outcome-tracking loop having run long enough to show whether its recommendations worked. Expect the sharing surface to grow permissions and expiry controls next, since a link that works without an account is the first place governance pressure lands.

F
fmtr
ANALYTICS
0.0

Rebuilding SAS's formatting layer in R, one format specification at a time

◆ Current state

fmtr applies formats to R data the way SAS applies them: named format catalogues, format lists, and an fapply() that maps a specification onto a vector. It is part of a family of packages that reconstruct SAS reporting idioms in R, and it shares infrastructure with them — labels.data.frame() was moved out to the common package, which fmtr now depends on. The recent releases have been closing specific gaps against SAS's own format vocabulary.

◆ Where it's heading

The direction is parity, pursued in small increments. Quarter format codes were added because base R has none; the SAS best. format was reimplemented, then hardened against the variations people actually write; statistical summary helpers like fmt_mean_sd() and fmt_mean_stderr() cover the cell contents clinical tables need. The structural work is largely behind it, including the breaking 2022 move that handed labelling to a sibling package, so what remains is vocabulary coverage.

◆ Prediction

The pattern of adding a SAS format, then a release to handle its variants, suggests the next releases continue filling in format codes and summary helpers rather than changing how formats are applied.

Alternatives to Basedash and fmtr

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 Basedash or fmtr.

See all Basedash alternatives → · See all fmtr alternatives →

Recent activity from Basedash and fmtr

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

  1. 2d agoBasedashIntroducing public sharing: live dashboards for anyone
  2. 5d agoBasedashIntroducing Tasks: your operations, on autopilot
  3. 6d agoBasedashA sidebar that follows what you’re working on
  4. 12d agoBasedashIntroducing Basedash Subscriptions
  5. 13d agoBasedashSort and arrange tables without changing the chart
  6. 19d agoBasedashIntroducing Basedash audit logs
  7. 10mo agofmtrMean and standard error helper, plus best-format variants
  8. 11mo agofmtrSAS best. format reimplemented in fapply()
  9. 2y agofmtrQuarter format codes %q and %Q added
  10. 2y agofmtrFormat lists become readable and writable files
  11. 2y agofmtrDocumentation and examples expanded
  12. 2y agofmtrvalue() can return results as a factor

Frequently asked questions

What is the difference between Basedash and fmtr?

They serve adjacent needs but don't currently overlap on shipped themes. Basedash is currently shipping more aggressively (velocity 7.5 vs 0.0), with 1 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 Basedash better than fmtr?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Basedash is currently shipping more aggressively (velocity 7.5 vs 0.0), with 1 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 Basedash?

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

What are the best alternatives to fmtr?

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