How much does Kadoa cost?
Kadoa uses freemium pricing. You can start for free, and paid plans move to usage-based billing after the trial period. Kadoa does not publish exact figures on a flat price list, so the cost depends on how much you extract and which features you need. Higher tiers add things like volume discounts, more connectors, and SSO for larger teams. Check the pricing page or talk to sales after starting a trial to get a number for your usage.
Is Kadoa open source or self-hostable?
Kadoa is closed-source, so you cannot inspect or fork the code. Its standard plans are hosted SaaS, but the Enterprise tier does offer on-premise and private-cloud deployment for teams that need to run it inside their own environment. Kadoa handles extraction, JavaScript rendering, and structure adaptation itself. If open code specifically matters, ScrapeGraphAI is open source and can be self-hosted instead.
Does Kadoa render JavaScript and handle dynamic pages?
Yes. Kadoa renders JavaScript and can extract from client-side pages, returning structured output without you writing selectors. It auto-detects page structure, which works well on standard, consistent templates. The auto-detection is less reliable on complex, heavily dynamic single-page apps, where results can need correction and customization options are limited. For predictable layouts it works well. For unusual SPAs, budget time to verify the output.
What is Kadoa best used for?
Kadoa targets enterprise and financial-services teams that need structured web data at scale, with real-time monitoring and change detection on sources like listings, filings, and pricing pages. The point-and-extract approach removes selector maintenance, and the AI re-learns when a layout changes, so it also suits less technical users. It is a weaker fit when you need fine-grained control over extraction logic, or when you are scraping irregular single-page apps where the auto-detection misfires.
How does Kadoa compare to Diffbot?
Both are closed-source extraction services in the agentic-extraction category. Kadoa offers on-premise or private-cloud deployment on its Enterprise tier, while Diffbot is hosted-only. Kadoa centers on a no-code interface: you point at a page and it generates the extraction logic, now aimed increasingly at enterprise and finance teams. Diffbot leans toward API-driven structured extraction at scale plus its knowledge graph, which suits engineering teams building data pipelines. Choose Kadoa for accessible collection with an enterprise deployment path, Diffbot for programmatic scale.
What is the best alternative to Kadoa?
It depends on the gap you are filling. ScrapeGraphAI is the strongest choice if you want open-source code you can self-host and customize. Diffbot suits teams needing API-first extraction at scale plus a knowledge graph. parse.bot is another agentic option worth comparing for natural-language extraction. If Kadoa's auto-detection struggles on your dynamic SPAs, or you need deeper control, these three are the most direct substitutes.
