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kernelshap vs Omni

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

kernelshap vs Omni: at a glance

FeaturekernelshapOmni
SectorAnalyticsAnalytics
Velocity score0.06.3
Sparks · 30d01
Top themesshap, model explainability, sampling algorithms, numerical correctnessbusiness-intelligence, semantic-model, ai-routines, mcp
Last editorial update4d ago23h ago
WebsiteVisit →Visit →

What is kernelshap?

kernelshap makes permutation SHAP practical past eight features, then fixes the kernel weights it had wrong.

kernelshap computes model-agnostic SHAP values in R through Kernel SHAP, permutation SHAP and an exact additive explainer. Version 0.8.0 added a sampling permutation-SHAP algorithm with standard errors and early stopping, lifting the practical feature ceiling past what the exact method allows. Version 0.9.0 then corrected a bug in how kernel weights were computed — exact Kernel SHAP now agrees with exact permutation SHAP — and moved parallelism from foreach to doFuture.

Read the full kernelshap trajectory →

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 →

kernelshap vs Omni: editorial side-by-side

K
kernelshap
ANALYTICS
0.0

kernelshap makes permutation SHAP practical past eight features, then fixes the kernel weights it had wrong.

◆ Current state

kernelshap computes model-agnostic SHAP values in R through Kernel SHAP, permutation SHAP and an exact additive explainer. Version 0.8.0 added a sampling permutation-SHAP algorithm with standard errors and early stopping, lifting the practical feature ceiling past what the exact method allows. Version 0.9.0 then corrected a bug in how kernel weights were computed — exact Kernel SHAP now agrees with exact permutation SHAP — and moved parallelism from foreach to doFuture.

◆ Where it's heading

Two concerns drive this package: making exact methods reach further, and being demonstrably right. The first shows in the additive explainer, the optional background dataset and the sampling permutation algorithm; the second in unit tests written against Python's shap, credited fixes from outside contributors, and a willingness to ship a correctness fix that changes numbers people have already published. Speed work runs continuously underneath — direct solves replacing the Moore-Penrose pseudo-inverse, roughly 10% less memory.

◆ Prediction

The 0.6.0 and 0.7.0 notes each promised a stable 1.0.0 that has not arrived; with the weighting bug fixed and parallelism reworked, a 1.0 release is the most plausible next step.

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.

Alternatives to kernelshap and Omni

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 kernelshap or Omni.

See all kernelshap alternatives → · See all Omni alternatives →

Recent activity from kernelshap and Omni

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

  1. 1d agoOmniOmni adds default filters on composite topics and query stopping
  2. 9d agoOmniOmni adds presentation mode and a searchDashboards MCP tool
  3. 16d agoOmniOmni adds AI credit controls per user and embed entity group
  4. 23d agoOmniAI semantic model generation goes generally available in Omni
  5. 1mo agoOmniOmni adds AI suggestion endpoints and OAuth for database connections
  6. 1mo agoOmniOmni brings AI routines to Slack and adds in-app MCP settings
  7. 1y agokernelshapKernel weight bug fixed; parallelism moves to doFuture
  8. 1y agokernelshapSampling permutation SHAP with standard errors
  9. 2y agokernelshapBackground data now optional; ranger survival support
  10. 2y agokernelshapFactor-valued predictions dropped
  11. 2y agokernelshapadditive_shap() explains additive models exactly
  12. 2y agokernelshapFaster on plain data.frames

Frequently asked questions

What is the difference between kernelshap and Omni?

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

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

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

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.