Web Datasets
Web datasets enable researchers, analysts, and developers to train models or conduct analysis using real-world data collected from public sources.
Best YouTube Datasets: Bright Data, Oxylabs & Grepsr ['26]
YouTube has become a primary source for training advanced multimodal AI and large language models (LLMs). However, obtaining YouTube data at scale remains difficult due to anti-bot measures and significant bandwidth requirements. This review examines key companies in the YouTube data sector: Bright Data, Oxylabs, Decodo, and Grepsr.
Amazon Dataset Comparison 2026: Bright Data, Oxylabs, Grepsr & Exellius
Bright Data and Oxylabs’ Amazon datasets are recognized as market leaders due to their scalable product archives. The industry has diversified into specialized niches. Exellius provides verified decision-maker contacts for B2B sales outreach, offering capabilities that exceed those of standard scrapers. Grepsr delivers a managed service focused on historical trend analysis.
LinkedIn Datasets in 2026: Best Sources for Profile & Company Data
LinkedIn datasets can be categorized into profile data and company data: We explore the best LinkedIn data providers and how to access structured datasets legally.
5 Best Social Media Datasets in 2026
We compared five leading social media data providers, focusing on the types of social data they offer and the platforms they include. Our evaluation finds vendors fall into two groups: those offering content-level social media data (posts, comments, engagement) and those providing profile- or identity-level data (social handles, professional profiles, company info).
Best Glassdoor Datasets in 2026
Glassdoor datasets offer valuable insights into job listings, employer reviews, and salaries, but they are not the exclusive source of labor-market or employer-brand data. In this article, we review the four top providers of Glassdoor datasets: Bright Data, Coresignal, Oxylabs, and Actowiz.
Sentiment Analysis Datasets in 2026
Sentiment analysis is a great way to understand the customers’ feelings toward a company and to see if they are associated with sales, investments, or agreements. Ensuring a reliable sentiment analysis depends on many factors, and one of its building blocks is the dataset used to train the models.