💡Fine-tuning or RAG — which dataset should I buy?

It depends on how the knowledge is used and how often it changes. For continuously refreshed facts, use RAG with a scraping API that revisits URLs on a schedule (~$0.50 per 1,000 results); to change what the model itself knows, buy a one-off structured dataset (JSON/CSV/Parquet) for fine-tuning. Most teams combine both; copyrighted content should not be loaded into training directly. Versus Bright Data's and Oxylabs' enterprise dataset quotes, Thordata lets you trial a small sample first.