Data Marketplace vs DX Network

Data Marketplace is a service for finding, evaluating, buying, and selling machine-ready datasets. Analysts can use its dashboard, while AI agents can use an API, REST endpoints, a hosted MCP server, or an OpenAPI specification to discover, query, and purchase data. Each dataset listing includes a machine-readable schema, data dictionary, and automated PII detection report. Buyers can preview 50 rows and filter by format, license, recency, and quality score. Uploads are scored for completeness, freshness, and consistency; after payment clears, purchased datasets can be downloaded as CSV, Parquet, or JSON. Buyers can post data requests with a reward, and providers can compete to fulfill them; payment is due only if the result meets the stated specification. Datasets are scanned for personal information before publication, but uploaders are responsible for having a lawful basis to share personal data. The terms call the service an early-access beta, with features that may change or be removed and no guarantee that data will be retained. The free plan costs nothing; Starter costs $19 a month.

DX Network is an infrastructure marketplace for buying and selling structured data in real time through an API. Its first Tech Industry marketplace covers technology companies, products, investors, investments and news. Buyers can request data combined across publishers in one API request, using DX/SPARQL semantic queries or wrapper endpoints. The network describes a subscriptionless, pay-as-you-go model that charges per datapoint through Ethereum payment channels and DX Tokens; the marketplace is free to try, but transactions use tokens. Its API documentation says Ethereum state channels handle authentication and payment. The maker says listed data is signed and transactions provide cryptographically secured provenance and integrity, while also stating that it makes no assumption about data quality or participant honesty. Buyers can whitelist or blacklist sources. The API and SDK are intended for integration into SaaS products, private apps and algorithms; developer materials include a Python library. The data model represents organizations, articles and products using an OWL 2 ontology. API access is listed for Linux, macOS and Windows.