Datasets that run on the Apify platform and are made to be called again and again: a strict output schema, explicit error records, and a price per delivered row. Failed rows are never charged.
Transcripts, comments, channels and charts in bulk, for AI pipelines and content research. 10 datasets.
Trends, autocomplete, news, jobs, shopping and local results, structured and repeatable. 15 datasets.
App Store, Google Play, Steam and Apple Podcasts metadata, rankings and charts. 3 datasets.
DNS, SSL, deliverability, tech stack, sitemaps, redirects and page extraction. 5 datasets.
Shopify and WooCommerce catalogues and store reports. 2 datasets.
SEC filings, finance quotes, careers pages, GitHub and Hacker News. 1 datasets.
How to pull this data, and where the free routes stop.
The free routes, the point where each one stops, and what it costs to pull transcripts for hundreds or thousands of videos.
What Google does and does not offer, why Trends numbers break when you compare them wrong, and the working routes.
Extensions, the official API and its quota, and how to pull comments for a whole channel without babysitting it.
The free RSS route, the Python route, and what changes once you need this every day without failures.
Why the indexing API is not what most people are looking for, and how to read Google for Jobs results instead.