whether you are buying data to avoid scraping or selling data you have collected, these are the platforms worth knowing in 2026, with honest assessments of pricing, data quality, and buyer/seller experience.
why use a data marketplace
scraping everything yourself costs time, infrastructure, and anti-bot bypass work. for common datasets (company firmographics, consumer demographics, financial data), buying from a marketplace is often cheaper than building the pipeline. on the sell side, marketplaces give scrapers a distribution channel without building a customer acquisition machine.
commercial data marketplaces
Snowflake Data Marketplace
the largest B2B data marketplace by revenue. strength is the zero-copy sharing model: data stays in Snowflake, you query it directly in your own account without ETL. 2,000+ listings across financial, demographic, weather, and alternative data. requires a Snowflake account (minimum $25/month on pay-as-you-go). best for: enterprise teams already in the Snowflake ecosystem.
AWS Data Exchange
Amazon’s data marketplace, integrated into S3 and AWS services. 3,500+ datasets. strong in financial data, healthcare, and satellite imagery. delivery is S3-based; you subscribe and data lands in your bucket. pricing ranges from free to $50,000+/month for premium financial feeds. best for: teams already on AWS who need automated data delivery into their pipelines.
Databricks Marketplace
newer than Snowflake but growing fast. similar zero-copy model for Delta Lake tables. strong in ML training datasets and AI-specific data products. if you are using Databricks for ML pipelines, check here before scraping training data yourself.
Datarade
a data marketplace aggregator that lists datasets from 1,000+ providers and lets you compare them. not a data host itself. search by data type, geography, update frequency, and delivery format. strong in B2B contact data, location data, and web data.
free and open datasets
Hugging Face Datasets
the default destination for ML training data in 2025-2026. 100,000+ datasets, free to download. strongest in NLP, computer vision, and tabular ML:
from datasets import load_dataset
ds = load_dataset("wikipedia", "20220301.en", split="train[:1%]")
print(ds[0]["text"][:500])Kaggle Datasets
130,000+ user-contributed datasets. best for: historical financial data, sports statistics, public health records, and competition datasets. API access via the kaggle CLI makes bulk downloading easy.
data.gov and equivalents
US federal datasets: 300,000+ datasets across all agencies. equivalent platforms: data.gov.uk (UK), data.gov.sg (Singapore), data.europa.eu (EU). strong in economic statistics, health data, geospatial data, and census data.
World Bank Open Data
macroeconomic and development indicators for 217 countries, 1960-present. the API is clean and well-documented. Python wrapper: wbgapi. essential for any economic research or content involving global statistics.
alternative data sources
Nasdaq Data Link (formerly Quandl)
financial and alternative data. free tier includes most economic data; premium tiers ($50-500+/month) cover equity fundamentals, options data, and alternative signals. useful for: backtesting, financial research, investment content.
Common Crawl
the largest freely available web crawl. monthly snapshots, 250-300TB of compressed data per crawl. hosted on S3 via AWS Open Data. process it with Athena, Spark, or the cdx-toolkit Python library for targeted queries. use this if you need historical web content without scraping it yourself.
selling your data
if you have built a proprietary dataset, the fastest path to revenue is Datarade (for B2B data buyers), Gumroad or Lemon Squeezy (for one-time CSV sales), or building a direct API product. niche datasets (e.g., weekly Amazon pricing data for a specific product category, daily SERP rankings for an industry) are more valuable than broad commodity datasets. see how to monetize web scraping for the full playbook.
sources and further reading
related guides
- how to monetize web scraping
- what is web scraping
- 25+ web scraping project ideas
- web scraping for data journalism
last updated: April 1, 2026