OpenCTI
OpenCTI is rebuilding its connector layer into a marketplace and wiring the platform to XTM Hub
A side-by-side editorial comparison of dbt Core and Geckoboard — release velocity, themes, recent moves, and the top alternatives to consider.
The Rust rewrite crosses from alpha to beta, and it can now bind SQL without touching the warehouse.
dbt is running two release lines at once. The 1.x Python line reached 1.12.0 in July, a GA that removed the experimental dbt login command and the bundled dbt-state plugin outright while adding the v2 semantic layer YAML parsing. The 2.0 Fusion line — the Rust engine — moved through five alphas and reached its first beta on August 10, carrying catalog-free binding, dbt state explain, redundant-test skipping, and a lint rule system that understands node selection.
Geckoboard is refining the dashboard itself — more filtering control and faster data.
Geckoboard's recent work targets the mechanics of building and reading dashboards: multi-value GA4 contains filters, cross-object HubSpot filtering, chart granularity decoupled from timespan, configurable week-start, and webhook-driven instant updates for Zendesk agent status. It also shipped a stacked column chart — its first entirely new visualization in years.
dbt is running two release lines at once. The 1.x Python line reached 1.12.0 in July, a GA that removed the experimental dbt login command and the bundled dbt-state plugin outright while adding the v2 semantic layer YAML parsing. The 2.0 Fusion line — the Rust engine — moved through five alphas and reached its first beta on August 10, carrying catalog-free binding, dbt state explain, redundant-test skipping, and a lint rule system that understands node selection.
Fusion is being built to do statically what dbt-core did by asking the warehouse. Catalog-free binding lets SQL bind without introspection, tests get skipped when they are provably redundant, and dbt State speculatively submits nodes while the dependency prefetch is still in flight — all of it trading round-trips for compile-time analysis. Meanwhile 1.x is absorbing the v2 semantic layer YAML piece by piece, which puts metrics and entities into the model graph itself. Adapter breadth keeps widening in parallel, with Databricks service principal auth, Redshift group grants, and ClickHouse materialization configs.
With beta.1 out, the next milestones are further betas hardening the Fusion feature set toward parity, and continued v2 semantic YAML work landing in the 1.x line.
Geckoboard's recent work targets the mechanics of building and reading dashboards: multi-value GA4 contains filters, cross-object HubSpot filtering, chart granularity decoupled from timespan, configurable week-start, and webhook-driven instant updates for Zendesk agent status. It also shipped a stacked column chart — its first entirely new visualization in years.
The direction is steady refinement of the core dashboarding surface rather than expansion into new product areas. Most releases give analysts finer control over how existing metrics are filtered, bucketed, and refreshed — closing small gaps power users hit daily.
Expect more of the same: incremental filtering, visualization, and integration-freshness improvements. The single new chart type may signal appetite for more visualizations, but the entries don't confirm a broader push.
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 dbt Core or Geckoboard.
OpenCTI is rebuilding its connector layer into a marketplace and wiring the platform to XTM Hub
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See all dbt Core alternatives → · See all Geckoboard alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. dbt Core 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dbt Core 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.
Top dbt Core alternatives in Analytics are ranked by recent ship velocity. Browse the "dbt Core alternatives" section above for the current picks, or visit /alternatives/dbt-core for the full list with editorial commentary on each.
Top Geckoboard alternatives in Analytics are ranked by recent ship velocity. Browse the "Geckoboard alternatives" section above for the current picks, or visit /alternatives/geckoboard for the full list with editorial commentary on each.