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Comparison · Analytics

Omni vs vellum

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

Omni vs vellum: at a glance

FeatureOmnivellum
SectorAnalyticsAnalytics
Velocity score6.35.0
Sparks · 30d10
Top themesbusiness-intelligence, semantic-model, ai-routines, mcpr-graphics, rendering-engine, linting, accessibility
Last editorial update1h ago3d ago
WebsiteVisit →Visit →

What is Omni?

Omni ships weekly, and almost every week the headline item is an AI feature.

Omni publishes a dated weekly digest whose body is a single line listing that week's items, so each entry compresses several releases into a sentence. Across the window the pattern is unmistakable: AI-powered semantic model generation reaching general availability, AI Routines creatable from chat and deliverable to Slack, AI model suggestion endpoints, AI credit controls scoped to embed entity groups and individual users, AI Evals on Azure, and MCP surfaces appearing both in-app and as a searchDashboards tool. The most recent week breaks that streak — default filters on composite topics, stopping a running dashboard query, full-screen preview editing — the first digest in two months led by conventional BI work.

Read the full Omni trajectory →

What is vellum?

vellum's bugs are now found by using it, not testing it — the downstream grammar is doing the QA.

The rendering engine shipped nine releases in the two weeks around the end of July, six of them on a single day. Almost every entry is a correctness fix in a capability that worked when drawn and failed when measured, or worked in isolation and failed in composition. The release notes are unusually forensic: each one states the mechanism, the observable symptom, and why the fix mirrors the draw path rather than reimplementing it.

Read the full vellum trajectory →

Omni vs vellum: editorial side-by-side

O
Omni
ANALYTICS
6.3

Omni ships weekly, and almost every week the headline item is an AI feature.

◆ Current state

Omni publishes a dated weekly digest whose body is a single line listing that week's items, so each entry compresses several releases into a sentence. Across the window the pattern is unmistakable: AI-powered semantic model generation reaching general availability, AI Routines creatable from chat and deliverable to Slack, AI model suggestion endpoints, AI credit controls scoped to embed entity groups and individual users, AI Evals on Azure, and MCP surfaces appearing both in-app and as a searchDashboards tool. The most recent week breaks that streak — default filters on composite topics, stopping a running dashboard query, full-screen preview editing — the first digest in two months led by conventional BI work.

◆ Where it's heading

Two things have been happening in parallel and they are related. Omni pushed AI into the modelling layer rather than only the query layer, which is what semantic model generation reaching GA signified, then built the commercial and access controls those features require — credit limits per user and per embed entity group arrived within weeks of the capabilities that consume them. The MCP work points at a third direction, exposing Omni's content to external agents rather than only serving its own chat. The latest week's return to filters and query controls suggests the AI surface has reached the point where the surrounding product has to catch up to it.

◆ Prediction

With searchDashboards already shipped as an MCP tool, more of Omni's catalog is the obvious next thing to expose that way, and credit controls should keep extending to cover newer AI surfaces. Whether the non-AI week is a pause or a genuine rebalancing is not something one digest can settle.

V
vellum
ANALYTICS
5.0

vellum's bugs are now found by using it, not testing it — the downstream grammar is doing the QA.

◆ Current state

The rendering engine shipped nine releases in the two weeks around the end of July, six of them on a single day. Almost every entry is a correctness fix in a capability that worked when drawn and failed when measured, or worked in isolation and failed in composition. The release notes are unusually forensic: each one states the mechanism, the observable symptom, and why the fix mirrors the draw path rather than reimplementing it.

◆ Where it's heading

The pivotal detail is stated outright in 0.6.3 — the first bug in the series found by using the engine from vellumplot rather than testing it in isolation. Every release since names the downstream as the source: the contrast rule's false positives, the lint rules that fired on all five sample plots, the keyed roundrect batch. A rendering engine with a real grammar built on top of it is now getting the integration coverage that unit tests structurally cannot provide, and the fixes are converging on one theme: the measurement path and the draw path must not drift.

◆ Prediction

Expect the release rate to fall as the vellumplot integration surface is exhausted, with remaining work concentrated in the lint rule set now that it is meant to gate builds rather than just inform.

Alternatives to Omni and vellum

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 Omni or vellum.

See all Omni alternatives → · See all vellum alternatives →

Recent activity from Omni and vellum

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

  1. 15h agoOmniOmni adds default filters on composite topics and query stopping
  2. 8d agoOmniOmni adds presentation mode and a searchDashboards MCP tool
  3. 15d agovellumLinter grows to 20 rules and stops firing on every plot
  4. 15d agoOmniOmni adds AI credit controls per user and embed entity group
  5. 16d agovellumAnimated SVGs no longer blink once and vanish or play in reverse
  6. 17d agovellumPick table now reports device pixels instead of two coordinate systems
  7. 18d agovellumContrast rule stops flagging every plot; gridlines become PDF artifacts
  8. 18d agovellumgrobwidth and grobheight now measure wrapped text, not the unwrapped line
  9. 18d agovellumKeyed roundrect becomes a real batch after downstream integration exposes it
  10. 22d agoOmniAI semantic model generation goes generally available in Omni
  11. 29d agoOmniOmni adds AI suggestion endpoints and OAuth for database connections
  12. 1mo agoOmniOmni brings AI routines to Slack and adds in-app MCP settings

Frequently asked questions

What is the difference between Omni and vellum?

They serve adjacent needs but don't currently overlap on shipped themes. Omni is currently shipping more aggressively (velocity 6.3 vs 5.0), 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 Omni better than vellum?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Omni is currently shipping more aggressively (velocity 6.3 vs 5.0), 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 Omni?

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

What are the best alternatives to vellum?

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