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You can build a B2B lead-candidate pipeline without Google Maps API charges by querying OpenStreetMap data with Overpass and processing the results in Python. The data is open under the Open Database License (ODbL), but that does not make public query services unlimited, guarantee complete business listings, or grant permission to contact the businesses you find.
What this pipeline can—and cannot—find
OpenStreetMap (OSM) is a community-maintained geographic database. It contains mapped features and tags, not a verified directory of every local business. Coverage and tagging vary by place and feature type, and a matching map feature is not proof that a business is still operating, fits your sales criteria, or has agreed to receive outreach.
For a small workflow, the useful distinction is between the data and the service used to access it. OSM data is available under the ODbL, but the OpenStreetMap Foundation says its public map website is not a free third-party map API or tile service. For read-only searches, OSM points users to Overpass; its editing API is intended for editing the map, not extracting data for a lead list.
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Choose the right OSM service for each job
| Option | What it does | Fit and constraints |
|---|---|---|
| Public Overpass API | Searches OSM map elements by tags, rough location, and other criteria. | Suitable for bounded read-only queries when your use fits shared-service guidance. The Overpass API project gives broad guidance of around 10,000 requests and less than 1 GB of downloads per day; these figures are not an SLA or guaranteed quota. |
| Public Nominatim | Geocodes place names and addresses; it is not a tool for enumerating all businesses. | The OSM Foundation Operations Working Group’s policy for its public instance limits use to at most one request per second, requires an identifiable User-Agent or Referer and attribution, and prohibits systematic all-POI queries. Those rules do not automatically apply to other providers or self-hosted instances. |
| Extracts or a self-hosted service | Provides a route for workloads that exceed public query-service guidance. | Consider this when you need regular or larger-scale querying. The Overpass global installation guide recommends 500 GB to 1 TB of disk for the global instance it describes; that is not a requirement for every local extract or small setup. |
These services solve different problems: Overpass selects mapped objects, while Nominatim converts an address or place name into a geographic result. Do not send personal or confidential data to public OSMF services.
Plan a narrow, useful query
- Set one geographic boundary. Choose a town, district, or other limited region rather than trying to collect an entire country or the planet. A bounded area keeps the first run manageable and makes it easier to inspect what the query returns.
- Define the business category you want. Identify the relevant OSM tags before querying. Tagging is community-maintained and may differ across locations, so a category query will not have uniform recall. Treat the results as candidates, not a complete census.
- Decide what qualifies as a candidate. Write down the fields or criteria your sales process needs, such as a usable name, location, or business classification. Keep this separate from any later sales qualification: a mapped feature alone does not establish that it is a good prospect.
- Keep the query bounded and purposeful. Request only the region and features needed for that task. Avoid repeated identical requests, mass lookups of individual elements, and stitching together boxes to harvest the whole planet; Overpass identifies these patterns as problematic for shared infrastructure.
Build the Python processing pipeline
Keep the Python workflow in distinct stages so you can inspect and rerun the parts that need attention. The outline below describes the implementation; it does not depend on a particular Python package or claim that a code sample has been tested.
- Request: submit the bounded Overpass query to a read-only Overpass service. Identify your client, cache results locally, and use restrained retry and backoff behavior when a service returns an error. Respect the selected service’s policies rather than treating a successful request as permission for unlimited polling.
- Parse: preserve each returned map element’s source identifier and tags along with the geometry or location data you need. Overpass returns OSM’s map data model; matching tags indicate how an element was mapped, not its present operating status.
- Normalize: make names and address fields consistent enough for review and comparison. Preserve the original tag values as well, so normalization does not erase what OSM actually supplied.
- Deduplicate: use the stable OSM element identity to prevent the same source feature from appearing repeatedly in one collection. If you later merge records from outside sources, keep that matching step separate and review uncertain matches instead of silently merging them.
- Review and enrich: flag missing or ambiguous fields for manual review. If you add phone numbers, email addresses, operating status, or other business information, record that it came from a separate source and confirm that source permits your intended use.
- Export: include retrieval date, source identifiers, relevant tags, and attribution information alongside the fields your team needs. Keep OSM-derived data distinguishable from independently sourced enrichment.
A practical export schema might include a source element ID, feature type, name as mapped, category tags, address or location fields when present, retrieval timestamp, review status, and a source/provenance field for each enrichment value. Missing data should remain missing rather than being presented as verified.
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Overpass is shared infrastructure. Its project documentation gives broad safety guidance of around 10,000 requests and below 1 GB of downloads per day, but those numbers are not a service guarantee or a target to consume. Repeated identical queries and individual-element mass lookups are discouraged. A public Overpass endpoint is also a poor default backend for a broad public app.
For a recurring or expanding workload, reduce unnecessary requests with local caching and query only what the workflow needs. If demand no longer fits public-service guidance, use suitable data extracts or consider running your own instance. Self-hosting transfers the operational burden to you; the global installation guide’s disk recommendation illustrates that a full-planet setup can require substantial resources.
The standard OSM tile service is a separate service from data queries. Its policy requires attribution, an identifiable client, and caching, and prohibits bulk tile downloads and offline prefetching. A lead pipeline that only needs records generally does not need to fetch map tiles.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Use Nominatim only for appropriate geocoding
Nominatim’s public OSMF service is primarily intended to support the OpenStreetMap search function. Its usage policy says, “No heavy uses (an absolute maximum of 1 request per second).” The policy also prohibits systematic queries, including downloading all points of interest in an area. That makes public Nominatim unsuitable for bulk geocoding or business enumeration.
If a small workflow genuinely needs to geocode a limited number of addresses, follow the public service policy: send no more than one request per second, identify your client with a User-Agent or Referer, provide attribution, and do not submit personal or confidential data. For regular bulk geocoding, use another provider or a self-hosted service whose terms and capacity fit the workload.
Handle ODbL attribution and redistribution deliberately
Credit OpenStreetMap and make the ODbL available as required when using OSM data. If you publish or distribute a database derived from OSM, it may need to be made available under ODbL terms. The exact treatment depends on how the OSM data is combined with other information and how the resulting database is shared, so assess the actual dataset and distribution model rather than assuming that adding outside records removes the obligations.
Keep provenance in your pipeline: retain the OSM source identifiers and tags, note when you retrieved the data, and distinguish OSM-derived fields from third-party enrichment. That makes attribution and later license review more practical; it does not replace checking the ODbL requirements for your particular use.
Check outreach rules separately from map-data access
An OSM listing does not grant consent to contact a business or an individual. The rules for direct marketing, privacy, and electronic communications depend on the target jurisdiction and the channel you use. Before turning candidate records into outreach, check the requirements that apply to your location, your recipients, and your planned contact method.
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