OpenCTI
OpenCTI is rebuilding its connector layer into a marketplace and wiring the platform to XTM Hub
A side-by-side editorial comparison of Appfigures and dbt Core — release velocity, themes, recent moves, and the top alternatives to consider.
| Feature | Appfigures | dbt Core |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 3.8 | 7.5 |
| Sparks · 30d | 1 | 2 |
| Top themes | app-analytics, agentic, aso, competitive-intelligence | dbt-fusion, rust-rewrite, static-analysis, semantic-layer |
| Last editorial update | 1d ago | 1d ago |
| Website | — | Visit → |
Appfigures just made its app-market data something an AI agent can query, not something you screenshot.
Appfigures has spent the last year widening what its estimates cover — iPad data folded into every download and revenue figure, state-level financials in the API, a 15-report App Intelligence suite for competitor research, and Leaderboards that rank apps by explicit metrics instead of opaque store charts. The August release changes who consumes all of that: a CLI built specifically for AI agents, with a hinting system to keep them from misreading the data. The product is no longer only a dashboard.
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.
Appfigures has spent the last year widening what its estimates cover — iPad data folded into every download and revenue figure, state-level financials in the API, a 15-report App Intelligence suite for competitor research, and Leaderboards that rank apps by explicit metrics instead of opaque store charts. The August release changes who consumes all of that: a CLI built specifically for AI agents, with a hinting system to keep them from misreading the data. The product is no longer only a dashboard.
The arc runs from data completeness to data access. First they closed gaps in the underlying estimates, then they built more ways to slice them, and now they are exposing the whole surface to agents that can investigate, compare, monitor, and act — including replying to reviews and adjusting Apple Ads campaigns. Each layer assumes the one below it is trustworthy, which is why the accuracy fixes (iPad coverage, keyword popularity, Google Play delay removal) came first.
Expect the agent surface to deepen before it widens — more write actions exposed through the CLI, and Leaderboards and App Intelligence reports made directly queryable by agents rather than only through the web reports.
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.
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 Appfigures or dbt Core.
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
Deequ ships GitHub tags whose release notes are one commit message long
See all Appfigures alternatives → · See all dbt Core 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 1. 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 1. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top Appfigures alternatives in Analytics are ranked by recent ship velocity. Browse the "Appfigures alternatives" section above for the current picks, or visit /alternatives/appfigures for the full list with editorial commentary on each.
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.