OpenCTI
OpenCTI is rebuilding its connector layer into a marketplace and wiring the platform to XTM Hub
A side-by-side editorial comparison of Deequ and Qlik — release velocity, themes, recent moves, and the top alternatives to consider.
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.
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.
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.
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 Deequ or Qlik.
OpenCTI is rebuilding its connector layer into a marketplace and wiring the platform to XTM Hub
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
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Qlik is currently shipping more aggressively (velocity 3.8 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. Qlik is currently shipping more aggressively (velocity 3.8 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 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.
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.