broom.helpers
After eleven quiet months, the tidier under gtsummary is back to absorbing model classes.
Comparison · Analytics
haze vs Lightdash
A side-by-side editorial comparison of haze and Lightdash — release velocity, themes, recent moves, and the top alternatives to consider.
haze vs Lightdash: at a glance
| Feature | haze | Lightdash |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 5.0 | 7.5 |
| Sparks · 30d | 0 | 2 |
| Top themes | mesh-processing, neuroimaging, interpolation, dependencies | business-intelligence, ai-agents, content-as-code, developer-experience |
| Last editorial update | 23h ago | 1d ago |
| Website | Visit → | — |
What is haze?
Mesh interpolation drops its custom fork dependency and sheds weight.
haze does per-vertex smoothing and interpolation on triangular meshes, aimed at mapping neuroimaging surface data between subjects, with k-d tree lookup and interpolation in C++. After three years dormant it has shipped twice in a month: a modernization pass to get through R CMD check, and now the removal of its dependency on a custom Rvcg build. It has never been on CRAN because of package size.
What is Lightdash?
Lightdash keeps handing authoring to outside agents and keeping the governed layer for itself.
Lightdash has spent two months rebuilding around agents rather than around its own web editor. Data apps are scaffolded and iterated locally with Cursor, Claude Code or Codex and uploaded for the instance to build; Deep Research runs multi-step investigations against the warehouse; content as code now covers charts, dashboards, spaces, permissions, virtual views, AI agents, automations, users, groups and roles. The conventional BI surface is still maintained — SQL Runner big numbers, filter groups, timezone handling — but it is no longer where new capability lands. The newest release is a CLI slug rename that keeps Lightdash and the local files in step.
haze vs Lightdash: editorial side-by-side
haze
5.0ANALYTICS
Mesh interpolation drops its custom fork dependency and sheds weight.
◆ Current state
haze does per-vertex smoothing and interpolation on triangular meshes, aimed at mapping neuroimaging surface data between subjects, with k-d tree lookup and interpolation in C++. After three years dormant it has shipped twice in a month: a modernization pass to get through R CMD check, and now the removal of its dependency on a custom Rvcg build. It has never been on CRAN because of package size.
◆ Where it's heading
Both recent releases point at the same obstacle. Needing a patched Rvcg meant users could not install from any normal source, and package size is the stated reason CRAN was ruled out at the first release; this release removes the first barrier and starts on the second by deleting unused data files. Nothing has been added to the interpolation surface since 2022.
◆ Prediction
The direction of travel suggests a CRAN attempt once the size problem is solved, though the package has not said so and the earlier note put it ten times over the limit.
Lightdash
7.5ANALYTICS
Lightdash keeps handing authoring to outside agents and keeping the governed layer for itself.
◆ Current state
Lightdash has spent two months rebuilding around agents rather than around its own web editor. Data apps are scaffolded and iterated locally with Cursor, Claude Code or Codex and uploaded for the instance to build; Deep Research runs multi-step investigations against the warehouse; content as code now covers charts, dashboards, spaces, permissions, virtual views, AI agents, automations, users, groups and roles. The conventional BI surface is still maintained — SQL Runner big numbers, filter groups, timezone handling — but it is no longer where new capability lands. The newest release is a CLI slug rename that keeps Lightdash and the local files in step.
◆ Where it's heading
The split is deliberate: authoring and interrogation move outward to whatever agent the user already runs, while the governed metrics, permissions and build stay inside Lightdash. The slug-rename command is a small marker of how far that has gone — refactoring tools are now needed for the repository rather than for the web UI, because that is where the content lives. Deep Research extends the same bet from generating artifacts to conducting analysis, testing competing explanations and validating numbers instead of emitting a chart.
◆ Prediction
Expect more repository-side maintenance commands of the slug-rename kind — moves, deletes, bulk edits across content-as-code files — since the agent workflow now produces content faster than the CLI can tidy it.
Alternatives to haze and Lightdash
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 haze or Lightdash.
OpenHouse
OpenHouse starts adding per-column defaults while still closing silent-failure holes.
Distributions.jl
Julia's distribution library keeps filing down the edges where sampling meets array types
Power BI
Power BI's monthly grind: authoring defaults, DAX documentation, and mobile finally catching up.
ggquiver
ggquiver is awake again, fixing arrow scaling that quietly misread irregular data.
vecvec
A lazy vector container keeps closing the gaps where it quietly materialised anyway.
See all haze alternatives → · See all Lightdash alternatives →
Recent activity from haze and Lightdash
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agohazeVersion 0.4.0 -- Remove dependency on custom Rvcg version
- 2d agoLightdash📝 Rename chart slugs safely
- 8d agoLightdashDeep research ⚡
- 17d agoLightdash🤖 Build data apps locally with your favorite agent ⚡
- 21d agoLightdash📦 More content as code
- 21d agoLightdashSQL Runner: Big Number
- 22d agohazeVersion 0.3.0 -- Fixes and modernization
- 25d agoLightdash🎯 Ask for one filter, not every filter
- 4y agohazev0.2.0 -- kdtrees
- 4y agohazeInitial release: mesh smoothing and k-d tree interpolation ⚡
Frequently asked questions
What is the difference between haze and Lightdash?
They serve adjacent needs but don't currently overlap on shipped themes. Lightdash is currently shipping more aggressively (velocity 7.5 vs 5.0), 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.
Is haze better than Lightdash?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Lightdash is currently shipping more aggressively (velocity 7.5 vs 5.0), 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.
What are the best alternatives to haze?
Top haze alternatives in Analytics are ranked by recent ship velocity. Browse the "haze alternatives" section above for the current picks, or visit /alternatives/haze for the full list with editorial commentary on each.
What are the best alternatives to Lightdash?
Top Lightdash alternatives in Analytics are ranked by recent ship velocity. Browse the "Lightdash alternatives" section above for the current picks, or visit /alternatives/lightdash for the full list with editorial commentary on each.