Executive Summary

Many analytics teams (estimates: ~100,000 teams) and growing numbers of dedicated analytics engineers spend hours each week tracing failures and dependencies in dbt projects because current UIs and docs are static, fragmented, and don't support fast, interactive debugging. This leads to slow incident resolution, opaque change impact, and wasted engineering time on relatively low-value detective work. You could build an open-source-first interactive lineage and project explorer tailored to dbt: a visual, searchable graph with live lineage, schema diffs, test-failure hotspots, CI integration, and a hosted product that layers access control, collaboration, and performance analytics on top. The product would integrate with cloud warehouses and open metadata standards so teams can try locally and upgrade to hosted features for ~ $20K ACV. The market is attractive right now — we estimate a $2.0B addressable market (100k teams × $20K ACV), with tailwinds from more analytics engineering specialization, cloud-native warehouses, and preference for trying OSS before buying (market score 86/100, revenue potential 80/100). Product-led growth is realistic if the OSS project demonstrably reduces time-to-debug and surfaces immediate value. You can differentiate by focusing on developer UX (fast, precise root-cause workflows, dbt-native metadata) and an OSS-to-hosted funnel that adds collaboration and security features, but expect real work integrating with varied warehouses, proving reliability against incumbent lineage tools, and building enterprise trust to convert free users to paying customers.

Market Opportunity

Visualize and explore dbt projects and lineage to speed debugging targets a $2.0B = 100,000 analytics/data-engineering teams × $20K ACV (analytics tooling, lineage and developer productivity spend) total addressable market with medium saturation and a year-over-year growth rate of 15% YoY — estimated growth for data tooling and analytics engineering spend as dbt and cloud warehouses expand (industry analyst synthesis).

Key trends driving demand: Rising analytics engineering specialization — more companies hire dedicated analytics engineers which increases demand for tooling built for their workflows.; Shift to cloud warehouses and modular stacks — cloud-native warehouses and open metadata standards make it easier to build integrations and ship hosted features quickly.; Open-source-first adoption for platform building — teams prefer trying OSS tools locally before buying hosted versions, which speeds product-led growth.; Increased focus on lineage and reliability — regulatory and business needs push teams to invest in lineage and provenance tools to reduce incidents..

Key competitors include dbt Cloud (dbt Labs), DataHub, Monte Carlo.

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Visualize and explore dbt projects and lineage to speed debugging

Executive Summary

Market Validation

Market Opportunity

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