Datadory notebook

How E-commerce Operators Use Rail Transportation Data

1,744 datasets. Pick your catch. Every guide here is built on what the catalog can actually prove.

1,744 datasets. Pick your catch.

Which delivery promises does a rail-adjacent e-commerce operation actually have to keep?

If you sell online in Europe, rail is closer to your order book than it looks. Parcel networks hand off to and from rail trunk legs, click-and-collect lockers sit inside stations, and a single afternoon of signalling disruption can push every 'arrives Thursday' promise on the affected corridor back a day. Most merchandising teams model none of this because the data sat behind operator press offices. It no longer does.

The open layer is broad enough to plan against. Datadory catalogs 17 rail transportation datasets - 15 primary plus 2 related - and 12 of those 15 primaries are free, with 7 offering an official API. Of the 1,744 datasets Datadory catalogs overall, 865 are tagged relevant to e-commerce operators; rail is a thin slice of that shelf, but the pieces that matter are the ones your competitors are not watching. The four uses below cover nearly all of the commercial value: station catchment sizing, live ETA adjustment, cross-border freight benchmarking, and network mapping for expansion screening.

The persona mismatch is worth naming. E-commerce operators hunt for price feeds, assortment breadth and demand signals; Datadory's tagging finds four rail datasets relevant to this persona at relevance 1 rather than the strong fits apparel-retail or marine-ports-services carry. Treat that as an instruction to use rail data surgically: it will not run your merchandising stack, but each of the four jobs below has a named, free source behind it.

Where should your next pickup point or concession go - and which dataset answers that?

Station footfall is published, not guessed. The SNCF Open Data Portal lists annual ridership for about 3,000 French stations covering 2015 to 2024, downloadable as CSV under commercial delivery terms with attribution. Pair it with the portal's national GTFS and NeTEx timetables, which roll 151 days ahead, and you get both how many people pass a gare and which trains they can catch - the two inputs a click-and-collect or locker placement model needs.

For Germany, the DB Open Data and DB Developer Portal supplies StaDa and OpenStation master data for roughly 5,400 stations under commercial delivery terms 4.0 and commercial delivery terms respectively, so geocoded coordinates for join work are free there too.

One caution when comparing countries. SNCF counts per-station annual validations across a national TGV/Intercités/TER scope, while ORR aggregates entries and exits by operator, sector, route and period rather than publishing passenger-level rows. Both are station-indexed enough for ranking; neither is a footfall counter at the door. Weight your model by service frequency from GTFS before committing lease budget, and let DB's StaDa coordinates handle the German join.

Can live train feeds really move your delivery ETAs?

The practical pattern is narrow. Poll Darwin for the stations your parcels actually transit, watch the incident feed for corridor-level messages, and widen promised windows when disruption hits rather than blanket-buffering every postcode. SNCF's GTFS-RT and SIRI feeds refresh every two minutes for France; Deutsche Bahn's FaSta API reports elevator and escalator status in real time, which matters if your pickup point sits behind a station concourse step change. opentransportdata.swiss archives 117 twice-weekly GTFS ZIP snapshots covering Timetable 2026, so Swiss schedule changes can be diffed instead of discovered.

Which network map tells you where rail-served fulfilment is physically possible?

Expansion screening starts with geometry. The NTAD North American Rail Network Lines from FRA/BTS maps all 302,771 North American segments at 1:24,000 or better, each carrying ownership, trackage rights, STRACNET designation and passenger flags, exported as Shapefile, GeoJSON, KML or CSV under unrestricted public-domain terms (a roughly 164 MB GeoJSON). If you are evaluating a US or Mexican 3PL, checking whether a candidate site touches a passenger-flagged or STRACNET line takes minutes.

OpenRailwayMap - Global Railway Infrastructure renders worldwide OpenStreetMap rail elements in five styles - infrastructure, maxspeed, signalling, electrification and gauge - under commercial delivery terms 1.0 with the attribution line 'Rendering: OpenRailwayMap'. Electrification and gauge styles answer a question parcel teams rarely think to ask until a rail-linked distribution option appears: what can actually run through a corridor. Bulk users should pull Overpass queries or planet extracts rather than hammering tiles.

Pick up where this leaves off

Every one of these ships with sample rows before you commit to anything.

Rail Transportation France - national TGV/Intercites/TER scope

SNCF Open Data Portal

Rail Transportation Great Britain national rail network, with operator-level…

ORR Data Portal - UK Rail Statistics

Rail Transportation Great Britain national rail network - England

National Rail Data Portal (UK)

Rail Transportation Germany nationwide - the DB InfraGO / DB Station&Service…

DB Open Data and DB Developer Portal

Rail Transportation EU27 aggregate plus EU

Eurostat Railway Freight Transport Statistics

Rail Transportation Worldwide - roughly 100-plus economies and aggregates…

World Bank Railways Goods Transported Indicator

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Questions worth asking

Is rail transportation data useful if my store never ships by train?

Indirectly, yes. Station ridership series such as SNCF's coverage of about 3,000 French stations and ORR Table 1223 tell you where click-and-collect demand concentrates, while Eurostat freight tables signal when inland capacity tightening will show up in carrier quotes. Delivery reliability and pickup-point economics are e-commerce problems even when wagons are not.