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 Qlik — 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.
Qlik feed is all marketing — events, webinars, and a subscribe CTA, no product changelog content.
The captured feed contains zero product release notes. All four entries are marketing content from qlik.com pages: the AI Reality Tour event series (May–Oct 2026), AWS Summits 2026 attendance, an open lakehouse ROI webinar, and a generic newsletter subscribe CTA. The actual product-updates blog at qlik.com/blog/category/product-updates/ is referenced but its entries did not land in the feed.
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.
The captured feed contains zero product release notes. All four entries are marketing content from qlik.com pages: the AI Reality Tour event series (May–Oct 2026), AWS Summits 2026 attendance, an open lakehouse ROI webinar, and a generic newsletter subscribe CTA. The actual product-updates blog at qlik.com/blog/category/product-updates/ is referenced but its entries did not land in the feed.
From the marketing posture alone, Qlik is positioning around enterprise AI scaling and open lakehouse architecture — both consistent with a vendor reframing legacy BI as an AI-native data activation platform. But without the product-updates feed, there is no observable product trajectory to comment on. The data on hand cannot support a confident read on where the product itself is heading.
The actionable next step is on the data-collection side, not the product: point the crawler at qlik.com/blog/category/product-updates/ or the Qlik Cloud release notes RSS so future runs have real changelog material. Until then commentary will repeat the 'all marketing' verdict.
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 Qlik.
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 Qlik 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 3.8), 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 3.8), 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 Qlik alternatives in Analytics are ranked by recent ship velocity. Browse the "Qlik alternatives" section above for the current picks, or visit /alternatives/qlik for the full list with editorial commentary on each.