DataMerge vs People Data Labs
People Data Labs offers massive-scale person data for data science and ML. DataMerge offers trade register verified company data from 170+ countries, legal name resolution, and corporate hierarchy. Both are developer-friendly, but they solve different problems. Sign up, get 20 free credits, and start enriching in minutes. Self-serve from $15/mo.
Quick Comparison
| Feature | DataMerge | People Data Labs |
|---|---|---|
| Global trade register data | ✓ | ✗ |
| Legal name resolution | ✓ | ✗ |
| AI domain matching | ✓ | ✗ |
| Corporate hierarchy | ✓ | ✗ |
| Person records at scale | Contact waterfall | ✓ 3B+ records |
| Bulk data licensing | ✗ | ✓ |
| MCP server for AI agents | ✓ | ✗ |
| Self-serve pricing | ✓ From $15/mo | ✓ Free tier |
Where DataMerge Wins
Trade Register Data from Government Sources
People Data Labs aggregates company data from public web sources and commercial databases, giving it broad coverage but without official verification. DataMerge pulls directly from government trade registers in 170+ countries, providing legally verified entity names, national registration IDs, registered addresses, and confirmed entity status. The difference matters when you need to trust the data. For compliance, KYB workflows, contract preparation, and legal verification, trade register data carries authority that web-scraped company profiles do not. PDL's 80M+ company records are broad, but DataMerge's 375M+ companies are verified at the source.
Legal Name Resolution and Corporate Hierarchy
DataMerge returns both the legal entity name and the display name as separate fields. PDL returns company names without this distinction. Beyond names, DataMerge maps full corporate hierarchies, showing parent companies, subsidiaries, and sibling entities across countries. If you need to understand that a prospect's local office in Berlin is a subsidiary of a holding company in London, DataMerge provides that structural data. PDL's company data is useful for firmographic context, but it does not model corporate relationships or distinguish between legal entities and trading names.
AI Domain-to-Entity Matching
Give DataMerge any domain and its AI resolves it to the exact legal entity, including local subsidiaries in specific countries. Search google.com with a DE preference and get Google Germany GmbH with its German trade register number. PDL can enrich a domain with firmographic data, but it does not perform intelligent entity resolution that accounts for country-specific subsidiaries. For teams that work across borders and need to identify the correct legal entity for each market, DataMerge's AI matching solves a problem that PDL's enrichment model was not designed to address.
MCP Server for AI Agent Integration
DataMerge offers an MCP server at mcp.datamerge.ai, enabling AI agents to query company data natively without custom API wrappers. As AI-powered sales, compliance, and research workflows become standard, having a data provider that integrates directly with AI agent frameworks is a real advantage. PDL has a solid traditional API but does not offer MCP integration. For teams building autonomous agents that need to look up, verify, or enrich company data as part of their reasoning chain, DataMerge's MCP server means one less integration to build and maintain.
Predictable, Accessible Pricing
DataMerge's pricing is straightforward: $15/mo annual, $19/mo monthly, or $40 for 200 pay-as-you-go credits. You know exactly what you are paying. PDL's pricing scales with volume, which can make costs unpredictable for teams running enrichment at scale. At high volumes, PDL's per-record pricing can become expensive quickly. DataMerge also gives you 20 free credits on signup with instant API access, so you can evaluate the data quality before committing to a paid plan.
Where People Data Labs is Strong
Massive-scale person data. People Data Labs has built one of the largest person-level datasets in the industry, with over 3 billion records covering employment history, education, skills, social profiles, and more. For data science teams training ML models, building recommendation engines, or running large-scale talent analytics, PDL's breadth of person data is genuinely unmatched. This is not marketing hyperbole. If you need millions of person records with rich biographical data for analytics or model training, PDL is purpose-built for that use case in a way that most data providers are not.
Developer-friendly from day one. PDL was built by developers for developers, and it shows. Their SDKs, documentation, and API design are clean and thoughtful. They offer client libraries in multiple languages, well-structured response schemas, and a sandbox environment for testing. For engineering teams evaluating data providers, PDL's developer experience sets a high bar. DataMerge shares this developer-first philosophy, but PDL deserves credit for being one of the earliest data providers to make developer experience a core product priority.
Bulk data licensing for data products. If your business model involves building data products, enriching large datasets for resale, or licensing data for third-party applications, PDL offers bulk data access that most API-first providers do not. You can license entire datasets for offline use, which is essential for companies that need to process data locally or build products on top of raw person data. DataMerge is optimized for real-time API enrichment, not bulk data licensing. For teams that need to download and process millions of records locally, PDL's bulk licensing fills a need that API-only providers cannot.
Who Should Use Which?
DataMerge is right if...
- You need trade register verified company data
- You need legal name resolution and corporate hierarchy
- You need AI domain-to-entity matching
- You are building compliance or KYB workflows
- You want predictable pricing from $15/mo
- You are building AI agents that need company data
- You need real-time enrichment through an API
- You need government-verified data, not web-scraped estimates
People Data Labs is right if...
- You need massive-scale person data for ML or analytics
- You need employment history, education, and social profiles
- You want bulk data licensing for data products
- Your primary use case is person-level enrichment at scale
- You are building talent analytics or recommendation engines
- You need to process millions of records locally
Frequently Asked Questions
How does DataMerge pricing compare to People Data Labs?
DataMerge starts at $15/mo on annual plans, $19/mo monthly, or $40 for 200 pay-as-you-go credits with instant API access. People Data Labs offers a free tier with limited credits and paid plans that scale based on volume. At low volumes, both are accessible. At higher volumes, PDL's per-record pricing can add up quickly, especially for enrichment-heavy use cases. DataMerge's pricing is simpler and more predictable, with no surprises as you scale.
Does DataMerge have trade register data that People Data Labs doesn't?
Yes. People Data Labs sources its company data from public web sources, commercial databases, and aggregated data sets. It does not pull from official government trade registers. DataMerge sources directly from trade registers in 170+ countries, providing legally verified entity names, national registration IDs, registered addresses, and confirmed entity status. For compliance, KYB, and legal verification workflows, trade register data provides a level of authority that web-sourced data cannot match.
Does DataMerge have an MCP server for AI agents?
Yes. DataMerge offers an MCP server at mcp.datamerge.ai that allows AI agents to query company data directly. This is designed for teams building autonomous AI workflows that need to look up, verify, or enrich company information in real time. People Data Labs does not currently offer MCP server integration. If you are building AI agents that need access to company data, DataMerge's MCP server provides native integration without building custom API wrappers.
Is People Data Labs better for bulk data?
For very large-scale data needs, yes. PDL offers bulk data licensing with 3B+ person records and 80M+ companies, which is useful for ML training data, large-scale analytics, and building data products. If you need to download millions of records for data science work, PDL's bulk licensing is designed for that. DataMerge is optimized for real-time enrichment and verification through its API, not bulk data dumps. The two products serve different ends of the data access spectrum.
How does the developer experience compare?
Both are developer-friendly. People Data Labs has good SDKs, clear documentation, and a well-designed API. DataMerge is also API-first with REST endpoints, comprehensive docs, and an MCP server for AI agent integration. The key difference is what you get back: PDL returns person-level data (employment history, education, social profiles), while DataMerge returns trade register verified company data (legal names, registration IDs, corporate hierarchy). Your choice depends on whether you need person data or company data.
When should I choose People Data Labs over DataMerge?
Choose PDL when you need massive-scale person data for ML training, data products, or analytics. PDL's 3B+ person records with employment history, education, and social profiles are genuinely impressive for data science use cases. Choose DataMerge when you need legally verified company data from government trade registers, legal name resolution, AI domain matching, or corporate hierarchy. Many teams use both: PDL for person-level data at scale, DataMerge for company verification and trade register data.
