Datamyne vs Panjiva Pricing, Coverage and Alternatives

The short answer: Panjiva and Descartes Datamyne are the two enterprise trade intelligence platforms, neither publishes a price, and they win with different buyers. Panjiva, owned by S&P Global, is stronger on entity resolution and analytics and is the usual pick for research, finance and investment teams. Datamyne, owned by The Descartes Systems Group, is stronger on landed cost modeling, denied party screening and Latin America, and is the usual pick for trade compliance and logistics. Most companies comparing them should first check whether a tier below either one answers the question.

Both were read on their own sites on August 23, 2026, and the most useful finding is not about features. It is that the headline coverage numbers these two vendors publish measure different things, so comparing them directly produces exactly the wrong conclusion.

Datamyne vs Panjiva at a glance

Figures come from datamyne.com and panjiva.com, read on August 23, 2026. Vendors revise these, so confirm before you sign.

Does Panjiva or Datamyne cover more of global trade?

This is the question buyers ask first and the one where the published numbers mislead. Panjiva states that it provides transactional data covering 35% of global trade flows. Datamyne's coverage hub says 75%+ of the world's import and export trade in its stat block, and the prose higher up the same page says about 85% of import trade by value and 85% of export trade, citing WTO-UNCTAD calculations.

Read quickly, that looks like 85% against 35% and Datamyne wins by a mile. It is not a like-for-like comparison. Panjiva is describing transactional data, meaning shipment-level records of individual consignments. Datamyne's percentage covers its whole database, and a large part of that database is aggregate census statistics rather than shipment records. Those are different products sold under one coverage number.

The distinction is not academic, because aggregate data carries no company names. If you buy on a coverage percentage and then discover the country you care about returns tonnages by HS code instead of suppliers, you have bought the wrong thing at enterprise price. Ask both vendors the same narrower question instead: for these specific countries, is the data declaration level with named parties, or is it census.

Which countries actually name companies?

Datamyne is unusually clear about this on its own regional pages, and the answer is worth writing down before any sales call.

Its European Union page describes Summarized Census Data, available for all member states, aggregate to the 6-digit HS code, arriving one to two months after receipt from official sources, with history back to 2007. Aggregate means no company names. Its Asia-Pacific page draws the line explicitly: census data for Australia, China, Japan and South Korea, and detailed import and export declarations that identify company names for India, Pakistan, Sri Lanka and Vietnam.

Counted from Datamyne's own sitemap on August 23, 2026, 54 countries have a dedicated coverage page, and 27 of them, exactly half, are EU member states. Add China, Japan, South Korea and Australia and at least 31 of those 54 countries return statistics rather than suppliers.

None of this is a failing on Datamyne's part, and Panjiva faces the same wall. No vendor can sell records a customs authority does not release. It is simply the fact that decides whether either subscription answers your question.

Can I find Chinese suppliers with Datamyne or Panjiva?

Yes, through the US import side rather than the China side. China does not publish shipment-level customs records naming the parties, which is why Datamyne's China coverage is census data and why every competitor has the same gap.

What exists is the other end of the same container. When a Chinese factory ships to Los Angeles, US Customs and Border Protection releases a maritime bill of lading naming the foreign shipper and the US consignee. That record sits in both platforms, and it is the actual mechanism by which anyone identifies Chinese manufacturers from trade data. ImportYeti built an entire free product on that one dataset.

Two limits ride along. The US route sees ocean freight, so air cargo and land-border trade from Mexico and Canada are thinner or absent. And a US importer may certify under 19 CFR 103.31(d) to have its name and address, and those of its shippers, withheld at source for a renewable two-year term. Every provider reads the same withheld set, so paying more does not recover those records.

How much do Datamyne and Panjiva cost?

Neither will tell you without a conversation. Datamyne has no pricing page at all; requesting one returns a 404, and every call to action is a demo request or the data specialist phone line. Panjiva routes pricing through S&P Global Market Intelligence. Both are annual enterprise subscriptions quoted by seats, countries and modules.

Two things follow for a buyer. First, scope tightly before the first call, because in modular enterprise pricing the quote moves with scope more than with any list price, and arriving without a country list means being sold the catalog. Second, get the specific countries and modules written into the contract rather than relying on the marketing coverage figure, for the reasons above. A quote-only annual contract also lands in the same budget line as the rest of your software spend, and if nobody is watching that line, read-only tracking of cloud and SaaS costs is a cheap way to stop five-figure renewals arriving as a surprise.

If you would rather price the category in thirty seconds, two vendors publish openly. Volza lists annual plans from a free trial up to 9,600 dollars a year, and ImportGenius publishes self-serve US tiers. Both are lined up against the enterprise pair in the roundup of import export data providers.

Which should a small business choose?

In most cases neither, and the reason is structural rather than budgetary. Both platforms are optimized for describing trade that has already happened across many companies. A small brand usually has the opposite question: one product, one first run of a few thousand units, and a need for someone who will actually quote it.

Shipment volume is also a poor filter for a small order. The factories that rank highest in customs data are the ones shipping containers, which means they are sized well above a first production run, and a good share of them will not quote you. Domestic manufacturers do not appear at all, because a US factory selling to US buyers generates no cross-border record.

The sensible ladder is to start with free US import search, move to a published-price tier when you can name the specific wall you hit, and reach the enterprise pair only when a team will use the platform daily. Most buyers who begin at the top are one or two tiers above their real question.

Do these platforms show prices, MOQs or lead times?

No, and this is the limit that matters most for anyone sourcing rather than researching. A customs filing records the shipper, the consignee, a date, a goods description, a weight and a container count. Unit price, minimum order quantity, lead time, current capacity and certification status appear nowhere in it. Those five things are most of a sourcing decision, and they only come from asking suppliers.

That is the gap an AI sourcing agent fills. You describe what you need to make or buy in plain English, and the agent finds and vets candidate manufacturers and returns a ranked shortlist with quotes, MOQs and lead times compared in one table, domestic or overseas. Vetting means identity verification, registry and customs cross-checks, surfaced certifications and risk flags shown with their evidence, which reduces risk rather than removing it. A sample order and your own judgment still belong in the process.

How the two tools work together

The teams that get the most out of trade data run it second, not first. Source forward, then verify backward.

Build the shortlist from your brief, so candidates are selected for being able to serve your order. Then take each name to the customs records and ask the questions only shipment data answers: does this company genuinely ship at scale, to which markets, how consistently, and to whom. That second pass catches the trading company presenting itself as a factory, since a real manufacturer usually shows a steady pattern within a coherent product category while a broker shows scattered descriptions across unrelated ones. Neither pattern is conclusive on its own, because plenty of legitimate manufacturers export through a separately named arm, so treat it as a question to raise rather than a verdict.

Used that way, a trade data subscription is a verification layer on a shortlist you already trust, which is a far cheaper thing to buy than a discovery engine doing a job it was not designed for. For the full sequence before money moves, how to vet a supplier covers what to confirm and in what order, and the individual platforms are broken down at Datamyne alternatives and pricing and Panjiva alternatives.

The bottom line

Pick Panjiva if a research, finance or market intelligence team will use it daily and you need resolved entities and feed delivery into your own stack. Pick Datamyne if you sit in trade compliance or logistics, want landed cost and denied party screening alongside the data, or care about Latin America. Expect a sales call and a four to five figure annual commitment either way, and get your country list in writing rather than trusting a coverage percentage. If what you actually need is a supplier who will quote your order, the answer is not on this page at all, and a database is not the tool.