Best Sources for Geospatial Datasets

Geospatial data spans a wide range of formats and use cases, from the roads and administrative boundaries that make up a base map to the points of interest, foot-traffic patterns, and mobility signals that power logistics and site-selection decisions. Because the category is so broad, picking the right source starts with being specific about what kind of geospatial data you actually need.

The Main Types of Geospatial Data

Base maps and boundaries cover roads, rivers, coastlines, and administrative divisions (countries, states, postal codes, census tracts). This is the foundational layer most mapping products are built on.

Points of interest (POI) data describes named locations: restaurants, retail stores, offices, landmarks. POI datasets typically include name, category, address, coordinates, and sometimes hours or contact details.

Mobility and foot-traffic data captures movement patterns, often derived from anonymized and aggregated mobile device signals. This category supports use cases like retail site selection and trade-area analysis.

Satellite and imagery data includes raster layers used for land-use classification, agriculture monitoring, or change detection over time.

Each of these categories has a different mix of free and commercial sources, and conflating them is the most common mistake buyers make when evaluating geospatial data.

Free Sources: What They Cover Well

OpenStreetMap is the standout free source for base map data. Its road network and boundary data are strong in most developed markets and increasingly detailed in many emerging markets thanks to active local mapping communities. Government open data portals also frequently publish administrative boundary files, especially for census geography and postal code shapefiles.

Where free sources tend to fall short is POI depth and freshness. A community-mapped dataset can have excellent coverage in one city and sparse coverage a few hundred kilometers away, depending on how active local contributors have been. If your product depends on consistent POI coverage across many regions, treat OpenStreetMap as a strong starting point rather than a complete solution.

When to Pay for Commercial Geospatial Data

Commercial geospatial data providers add value in a few specific ways: broader and more consistent POI coverage, structured business attributes (categories, hours, chains), update frequency guarantees, and access to mobility or foot-traffic signals that simply don’t exist in public datasets. If your use case depends on any of these, budget for a paid source rather than trying to stretch free data further than it can go.

Web data platforms such as Bright Data and Oxylabs offer collection infrastructure that can be used to build custom location datasets — for example, gathering structured business listing data from public web sources at scale, subject to the target sites’ terms of service. This is a common approach when off-the-shelf POI datasets don’t cover a specific vertical or region well enough, but it requires more engineering effort than buying a ready-made dataset.

Evaluating Regional Coverage Depth

Don’t take “global coverage” claims at face value. Ask providers for a coverage breakdown by country or region, and if possible, request a sample for the specific geography your product targets. Coverage depth varies enormously between North America/Western Europe and other regions, even among providers marketing themselves as global. For POI data specifically, check whether the source distinguishes between chain locations (which are usually well documented) and independent local businesses (which are harder to track and more prone to becoming stale).

Licensing and Attribution Considerations

OpenStreetMap is distributed under the Open Database License (ODbL), which includes a share-alike requirement: if you produce a derivative database from OSM data, you generally need to make that derivative available under the same license, and you must provide attribution. This has real implications if you’re building a commercial product on top of OSM data — read the ODbL terms carefully and consult legal counsel if your use case involves substantial modification or redistribution of the underlying data, rather than just rendering a map.

Commercial geospatial datasets typically come with clearer, more restrictive licensing that specifies exactly how you can use, store, and redistribute the data. Always review the license terms for redistribution rights, especially if your business model involves reselling processed geospatial data rather than just using it internally.

Combining Free Base Layers with Commercial POI Data

A practical and increasingly common architecture looks like this: use OpenStreetMap (or a government source) for the base map layer — roads, boundaries, geocoding reference data — and layer in a commercial POI or mobility dataset for the business-specific attributes your product needs. This keeps your base map costs low while concentrating spend on the data that’s genuinely hard to source for free.

When combining sources, standardize on a common coordinate reference system and a consistent geocoding approach early, since inconsistent geocoding between layers is one of the most common causes of data quality issues in production.

Matching Sources to Use Cases

• Logistics and routing: OpenStreetMap road networks are usually sufficient, supplemented by commercial traffic data if real-time routing accuracy is critical.
• Retail site selection: Combine boundary/demographic data with commercial POI and, ideally, foot-traffic or mobility data to model trade areas realistically.
• Consumer mapping products: A free base layer plus a commercially licensed POI dataset for search and discovery features is the standard approach.
• Custom research or one-off analysis: Free sources are often sufficient, especially for academic or internal-only projects with no redistribution requirements.

Next Steps

If you’re evaluating providers for your project, start in our Geospatial Data category to see how OpenStreetMap compares with commercial alternatives, and review the Get Geospatial Data use case page for a breakdown of buying paths by project type. For teams considering custom collection of location or business listing data, the web data platforms listed under Bright Data and Oxylabs are worth evaluating alongside off-the-shelf datasets — just make sure any custom collection approach respects the target sites’ terms of service and applicable data protection law.