What a Funding Database Actually Stores (and Why Schemas Decide the Comparison)
A funding database is not a list of companies. Underneath it is a set of linked record types: an entity record for each company, a round record for each financing event, an investor record for each firm or angel, and join records connecting investors to rounds with a role such as lead or participant. The schema decides what a comparison can even mean. Two products can both claim to cover the same market while modeling a round differently. One treats a seed extension as a separate round; another appends it to the original and revises the amount. One stores a single amount; another separates target, raised to date, and current tranche. One lets a company hold many active rounds at once; another closes the prior record automatically. Before comparing coverage, read each vendor's schema documentation and write down how it defines a round, a lead, a stage and a valuation. Otherwise you are counting different objects and calling one of them wrong.
Four Collection Methods Behind the Numbers, and What Each One Misses
Ask which collection methods sit behind a product's records, because each one carries its own blind spot. Regulatory filings, such as a US exempt offering notice or a share allotment record at a national companies registry, are authoritative where they exist; their limits come from the rule, not the vendor, so read the form's own instructions to see whether the amount field means the offering being made or the amount already sold, and check the filing deadline to learn how late a record can legally arrive. Press announcements carry context and speed, but only cover deals someone chose to publicize, at the figure the company chose to market. Contributor profiles reach the long tail and decay unless someone maintains them. Direct investor feeds are precise for a participating firm's own portfolio and silent about everything else. Ask each vendor for the source mix country by country, since a filings-heavy method in one jurisdiction has no counterpart where no filing exists.
Match the Database to the Question: Benchmarking, Sourcing, Market Mapping, Diligence
Write the question before the shortlist. Benchmarking a round needs accurate dates, clean stage labels, and enough comparable deals in your sector and geography to form a distribution worth quoting. Sourcing needs freshness, alerting on new rounds, and reliable linkage from company to founders and domains. Market mapping needs taxonomy quality and long-tail completeness, since the companies you have never heard of are the point. Diligence needs provenance: a link back to the filing or article behind every field, so a number can be defended rather than repeated. Once the job is named, scope the comparison explicitly across five axes: geography, stage floor, sector taxonomy, time depth, meaning how far back the round records stay reliable, and entity types included, such as whether angels, accelerators, family offices and corporate venture arms are modeled as investors. Score each candidate per axis instead of overall, so a win on geography does not cancel a loss on time depth.
Field-Level Comparison: Where Two Funding Databases Quietly Disagree
Disagreements rarely announce themselves. Dates split three ways: announcement, close, and filing. Valuation may be pre-money, post-money, or an unlabeled figure that is disclosed in one record and computed in another from the amount and an assumed dilution. Amounts may represent the full round, a first tranche, or cumulative capital to date, and a converted currency depends on which day's rate was applied. Stage labels drift, since pre-seed, seed and bridge conventions are not standardized, and a label may only mirror the wording of the announcement it came from. Instruments differ too: priced equity, convertible note, SAFE, venture debt and grants are sometimes pooled into one round record. Lead attribution varies where co-leads exist or where no lead was named. Build a crosswalk table mapping each field across candidates, and for every field record whether the value is sourced, derived, or estimated. Then ask each vendor whether estimated values carry a flag you can filter on before aggregating.
Running a Head-to-Head Bake-Off Against a Gold-Standard Sample
Use trial access to run a scored test, not to browse. Assemble a sample of rounds you can verify yourself: your own portfolio companies, customers whose raises you witnessed, or deals whose filings you can pull directly. Include the hard cases on purpose: a foreign-domiciled entity, a pre-seed SAFE, a round that closed quietly and was never announced, a company that renamed after its raise, a bridge stacked onto an earlier seed, and one acquisition that ends the round history. Freeze the sample and the evaluation date, then run every candidate against the identical list in the same week. Score three things separately: recall, meaning the round exists at all; field accuracy on amount, date, stage, lead and valuation; and lag, the days between the round becoming public and the record appearing. Log each disagreement with the field it hit and a suspected cause, because the shape of that error table tells you more about fit than a coverage headline.
Failure Modes: Double Counting, Duplicate Entities, Survivorship and Stale Records
Double counting shows up when an extension announced separately is later merged into the parent round, when a tranche is recorded as a full round, or when the same deal appears twice under two currencies. Duplicate entities follow renames, redomiciliation, holding company structures and legal-suffix variants, and each duplicate splits one company's round history in two. Survivorship is a risk to test rather than assume: ask whether records for companies that shut down are re-checked on the cadence used for active ones, then compare a set of shutdowns you know against each candidate, since a gap there bends every historical aggregate you build. Staleness concentrates in fields that change without a public event, such as headcount, status and website, so ask what a status of active asserts: a dated re-check, or the absence of a recorded shutdown. Undisclosed amounts are subtler: an imputed figure summed alongside reported ones yields totals nobody can reconcile.
Access, Licensing and the Real Cost of a Funding Data Subscription
The seat price is one term among several that decide what a funding subscription costs you. Ask how the meter runs: per API call, per round record, or per company profile, and whether export caps reset monthly. Ask where the archive stops, since a product may sell current rounds and price historical ones separately. Then read the license, because it governs what you may do with a round record: internal analysis only, or reuse in an investor update, a portfolio page, a client-facing screen. Ask what you keep after cancellation, whether attribution must sit next to a displayed amount, and whether investor firm records carry different terms than company records. Ask the refresh cadence for new rounds, whether company and investor identifiers survive a rename, and whether crosswalks exist to registration numbers and domains, since without them each refresh forces a fresh matching pass you own. Request a sample API response and a bulk file, then test both against rounds you already track.
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