Fulcrum
Fulcrum is consolidating on Esri, with Google Maps gone September 1
A side-by-side editorial comparison of Cube and Deequ — release velocity, themes, recent moves, and the top alternatives to consider.
| Feature | Cube | Deequ |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 6.3 | 0.0 |
| Sparks · 30d | 0 | 0 |
| Top themes | semantic layer, embedded analytics, ai agents, governance | data-quality, spark, dqdl, jvm-library |
| Last editorial update | 3mo ago | 15h ago |
| Website | — | Visit → |
Cube ships Creator Mode and a Slack agent — embedded BI and agent surfaces in the same month.
Cube is shipping weekly across three coherent fronts: AI agent surfaces (Slack Agent for ad-hoc questions, Analytics Chat under the hood), embedded analytics (Creator Mode lets customers embed the full Cube app, not just dashboards), and the semantic-layer fundamentals (calculated fields in Explore/Workbook, workbook versions, custom chart palettes, refined filtering). Earlier in the period, data masking, the Viewer role, and scheduled-screenshot notifications rounded out the governance and distribution story.
Deequ ships GitHub tags whose release notes are one commit message long
Deequ is a data quality library for Spark, and it releases per Spark version — tags carry a -spark-3.5 or -spark-4.0 suffix, so the same code line ships more than once. The release notes are whatever the last commit message said, which here means each entry is a single line. Four releases landed in a month between March and April 2026, and only two of them contain any product change: a Range analyzer with DQDL rule support, and a processRowsTyped API for typed outcome access.
Cube is shipping weekly across three coherent fronts: AI agent surfaces (Slack Agent for ad-hoc questions, Analytics Chat under the hood), embedded analytics (Creator Mode lets customers embed the full Cube app, not just dashboards), and the semantic-layer fundamentals (calculated fields in Explore/Workbook, workbook versions, custom chart palettes, refined filtering). Earlier in the period, data masking, the Viewer role, and scheduled-screenshot notifications rounded out the governance and distribution story.
Two compounding bets: (1) the semantic layer + AI agent combination is the moat — every release deepens what an agent or human can do over governed data without writing SQL, and (2) embedding goes from "put a dashboard in your app" to "give your users a full BI app inside your product." These are complementary — Creator Mode is more compelling when the embedded experience can also answer questions in Slack and self-heal queries with calculated fields.
Expect Creator Mode to grow more embedding controls (white-labeling, role mapping, audit) since it's positioned for ISVs serving downstream customers. The Slack Agent likely gets siblings (Teams, in-app chat) and tighter wiring to dashboards so an agent can produce a chart, save it, and share it back. Calculated Fields expansion (filtered measures, more types) is already telegraphed in the release notes.
Deequ is a data quality library for Spark, and it releases per Spark version — tags carry a -spark-3.5 or -spark-4.0 suffix, so the same code line ships more than once. The release notes are whatever the last commit message said, which here means each entry is a single line. Four releases landed in a month between March and April 2026, and only two of them contain any product change: a Range analyzer with DQDL rule support, and a processRowsTyped API for typed outcome access.
The visible work points in one direction — making check results programmatically consumable rather than just readable. A typed outcome API and a rule language binding are what you build when Deequ is being called from a pipeline that reacts to the result, not from a notebook where a human reads it. The column-pruning override added alongside the Range analyzer suggests the same attention on the cost side, keeping analyzers from scanning columns they do not reference.
The entries are too thin to support a confident read of what comes next; the only clear pattern is that each change will ship separately against Spark 3.5 and Spark 4.0, so the version skew between those branches will keep widening.
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 Cube or Deequ.
Fulcrum is consolidating on Esri, with Google Maps gone September 1
Omni ships weekly, and almost every week the headline item is an AI feature
Four ODD Platform releases in two weeks, and not one of them changes the product
Baremaps got geoparquet and hillshading, then went quiet for eighteen months in incubation
Marquez spent 2024 turning a lineage store into a UI, then stopped releasing
Amundsen's last release was a config flag, and the feed has been silent for two years
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Cube is currently shipping more aggressively (velocity 6.3 vs 0.0), with 0 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. Cube is currently shipping more aggressively (velocity 6.3 vs 0.0), with 0 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 Cube alternatives in Analytics are ranked by recent ship velocity. Browse the "Cube alternatives" section above for the current picks, or visit /alternatives/cube for the full list with editorial commentary on each.
Top Deequ alternatives in Analytics are ranked by recent ship velocity. Browse the "Deequ alternatives" section above for the current picks, or visit /alternatives/deequ for the full list with editorial commentary on each.