Definite

The core argument Definite makes is arithmetic: five contracts and three engineers versus one platform you deploy into your own cloud. That's a real differentiator, not a slogan — the docs walk through self-hosting on AWS, GCP or Azure via the definite CLI, with backup/restore, compute profiles, network requirements, permissions and even an air-gapped image mirroring guide. For a company with data residency or security constraints that can't put a warehouse in a vendor's account, this is the part of the product that matters most. The second differentiator is Fi. Most AI query assistants return a chart and stop. Fi builds an app — sidebar, filters, KPI tiles, tables — and then attaches an inspector to every element that shows summary, facts, breakdown and the underlying SQL. That auditability is the difference between a demo and something a finance team will actually sign off on. Component-level editing means you can ask the agent to fix one chart without it rewriting the other eleven. Browser-native DuckDB-Wasm is the third leg: the scraped demo shows 4.2M rows loaded client-side from a lakehouse, 318 MB of columnar parquet, zero server round-trips. That's an unusual engineering choice and it's what makes sub-second search feel instant rather than merely fast. The honest weaknesses: credit-based pricing means compute and AI share one pool, so a team that schedules heavy jobs hourly can burn through 100 credits before month-end, and extra credits are $1 each with storage overage at $0.05/GB/month. Custom transformations are SQL-model based — if your pipeline needs heavy bespoke Python transformation beyond the Python Runner, this isn't the tool. Fine-grained hand-crafted dashboard design is weaker than a dedicated BI tool, and custom visualizations, embeddable charts, CRM syncs, webhook syncs and external syncs are marked "custom development" on lower tiers. Read that line on the pricing page carefully before assuming parity across plans.