Panjiva vs ImportYeti: Trade Data Compared for Sourcing

The short answer: Panjiva and ImportYeti read the same US customs filings, and they are built for opposite buyers. ImportYeti is free, covers more than 70 million US ocean import bills of lading from 2015 onward, and answers the question most people arrive with: which factories shipped to this American brand. Panjiva is S&P Global enterprise software with over 2 billion shipment records from 21 countries, resolved company entities, and a 13 million relationship graph, quoted through sales with no published price. If your output is a decision about one supplier, the free tool answers it. If your output is a report about hundreds of companies, only the paid one will.

That framing matters because the usual comparison, feature list against feature list, pushes people toward the expensive option for a question it does not answer any better. Both platforms are looking at the same government paperwork. Paying more buys you processing and breadth, not a clearer view of the one factory you care about.

What each platform actually is

ImportYeti launched as a free search engine over US ocean import records. It requested the bills of lading from US Customs under the Freedom of Information Act, indexed roughly 70 million of them going back to January 2015, and organized them by company so you can type a brand name and see the overseas suppliers that shipped to it. There are paid tiers now, listed on review aggregators in August 2026 from around 10 dollars a month billed annually up to roughly 50 dollars a month for exports and API access, with enterprise arrangements quoted separately. The core lookup stayed free.

Panjiva started in the same year as the problem, 2006, founded in New York by Josh Green and Jim Psota after Green could not find trustworthy information about overseas suppliers for tablet displays. S&P Global acquired it in February 2018 and it now sells as Panjiva Supply Chain Intelligence inside S&P Global Market Intelligence. The pitch is no longer supplier research. It is supply chain mapping, tier-two exposure analysis, and trade flow research for analysts and risk teams, delivered through a web app plus Xpressfeed, Snowflake, and API.

So one company drifted upmarket into analytics while the other took the original job and gave it away. Neither drifted by accident, and knowing which direction each went tells you most of what you need.

Panjiva vs ImportYeti compared

Read the last three rows together. On the two questions that decide a sourcing project, whether a domestic factory exists and what it will charge, the free tool and the enterprise platform are identical, and both are blank.

Is Panjiva worth it compared to a free tool?

It is worth it when your work product is analysis across many companies, and it is not worth it when your work product is a purchase order. Panjiva earns its price through entity resolution, 21-country coverage, export records, and bulk delivery into your own stack. If you are checking which factories shipped to one US brand, ImportYeti reads the same underlying customs filing and returns the same answer at no cost.

The entity resolution point deserves a plain explanation, because it is the whole justification for the price gap. Customs forms are typed by freight forwarders in a hurry. A single factory in Ningbo shows up as NINGBO XX PLASTIC CO LTD, NINGBO XX PLASTIC CO., LTD., NINGBO XX PLASTICS, and a handful of other spellings, occasionally with a different address each time. Goods descriptions are equally loose. Search a few hundred million records naively and you get pieces of one company scattered through your results with nothing linking them.

Panjiva spends its engineering effort fixing exactly that, which is why it can produce a relationship graph and why it gets used for policy research and risk exposure work. On a single lookup, that machinery is close to irrelevant. You already know which company you are searching for.

Can I find a supplier for free?

You can find suppliers that already ship to US importers for free, and that is a genuinely useful slice of the problem. What no free or paid customs tool gives you is a supplier that will quote your order. Shipment history proves a factory moved goods to somebody else. It says nothing about capacity today, minimum order quantity, price at your volume, certifications, or whether the factory is accepting new accounts.

This is the point where most first-time sourcing projects stall, and the shape of the failure is consistent. You identify the factory behind a brand you admire, you send an email, and either nothing comes back or you learn the minimum order is 50,000 units. That factory was built around container-scale customers. A 2,000-unit first run is not business it wants, and no depth of manifest history would have told you in advance.

Why can I not find a company on ImportYeti or Panjiva?

Usually one of four reasons, and only one of them is fixed by spending money. First, the importer has certified for manifest confidentiality with US Customs under 19 CFR 103.31(d), which lets a company withhold its name and address and request the same for its shippers. The certification runs two years and is renewable. When it is filed, the record never reaches any vendor, so an empty result on the free tool will be an empty result on the enterprise one.

Second, the company imports under a legal entity name that differs from the brand you searched. Third, it buys domestically, so no import record exists at all. Fourth, the goods arrived by air or came overland from Mexico or Canada, which ImportYeti in particular does not cover.

Only the fourth is a coverage problem that a paid platform improves. Treat an empty result as information rather than a data failure: a company that has filed for confidentiality treats its supply base as a competitive asset, which usually means the factories behind it are worth finding another way.

What about the middle of the market?

There is a tier between free and enterprise, and skipping over it is a common mistake in both directions. ImportGenius publishes its US pricing, adds export records, daily updates, alerting, structured export, and additional countries as paid add-ons. The detail that catches buyers out is that its entry plan carries only the last 12 months of US import history, and reaching back further moves you to a tier at roughly double the price. Volza competes on country breadth per dollar, and Descartes Datamyne sits closer to logistics and customs compliance workflows. All five are lined up on price and coverage in the roundup of import export data providers.

If you are weighing the paid options against each other rather than against free, the head-to-head on ImportGenius vs Panjiva works through pricing, coverage, and entity matching in more detail, and the Panjiva alternatives and pricing breakdown covers the institutional access route that occasionally makes the enterprise tier free. There is a matching write-up of the free option on the ImportYeti alternatives page.

Teams that go the bulk-export route usually run into a second problem quickly. Once several vendor feeds land in the same warehouse alongside your own order data, tracing which table came from which source and whether it actually refreshed this week becomes its own piece of work, and the bottleneck moves from the trade data vendor to your internal stack.

The gap both platforms share

Neither tool can see a US contract manufacturer that sells to American brands. It imports nothing, files no bill of lading, and does not exist in either database. The same holds for a machine shop in Michigan, a co-packer in Texas, and a cosmetics filler in New Jersey. This is structural. It is not a coverage gap that 2 billion records closes, and it has grown more expensive as tariff exposure has pushed US buyers into seriously comparing a domestic run against an imported one. Doing that comparison honestly means both options quoted on the same specification, and a customs database can only ever show you one side. The arithmetic is worked through in domestic vs overseas manufacturing.

The deeper limit applies even where coverage is perfect. A shipment record carries shipper, consignee, date, a rough goods description, weight, and container counts. Price, minimum order quantity, lead time, current capacity, certifications, and quality history are not on the form at any price point, and those are the facts a sourcing decision actually runs on.

How to use these tools well

The sequence that works reverses the usual one. Start with the brief rather than the database: the product, the specification, the first-run quantity and expected annual volume, the certifications you need, your target landed cost, and the date you need units on a dock. Run that through supplier discovery and get back candidates that can actually serve it, domestic and overseas together. That is what an AI sourcing agent is pointed at: matching on capability and willingness rather than on history.

Then use trade data as corroboration against the short list of names that came back with real quotes. Has this exporter shipped consistently for several years, or does one container account for its whole record? Does the goods description match what it told you it makes? Do its consignees fit the customer profile it described? Checking four or five specific names is exactly what the free tool is good at, and it is where a paid subscription is hardest to justify.

Finish with the parts no database covers: a sample order, a reference call, and a written agreement. Vetting reduces risk, it does not remove it. A supplier can verify cleanly, appear in customs records exactly as described, hold every certification it claims, and still miss a delivery date. Place a small first order and keep a second qualified supplier warm. The fuller checklist is in how to vet a supplier.

Which one should you pick

The honest summary is that this is not really a two-way comparison. It is a question about which job you are hiring a tool for. For research about companies, pick by budget and scale, and start free. For a decision about your own production run, both platforms are the wrong shelf.