Location data for your industry.
Turn German addresses into coordinates and demographic context. Explore how rastr can support your work in property, finance, analytics and infrastructure — with the analysis and decisions staying in your hands.
Real estate
An address tells you where a property is. It does not tell you about the people living in the surrounding area.
How rastr helps
Geocode a German property address and retrieve population, age structure and average household size for its associated grid cell. Add residential context to neighbourhood research and property-location comparisons.
A practical workflow
Check several candidate locations for a residential project. Compare the published age bands and household context alongside your own rental, transaction and property data.
Keep in mind: Grid-cell demographics do not describe a property's occupants. rastr does not provide property valuations, rental prices, purchasing power or building characteristics.
Financial services
A branch list or property portfolio shows your locations, but not their geographic distribution or local residential context.
How rastr helps
Use coordinates to map your locations in your own tools. Add population and age structure to compare branch sites or contextualise the regional distribution of a property-backed portfolio.
A practical workflow
Geocode candidate branch addresses, compare their associated residential grid cells, then combine those results with your own service-area and customer data. Broader catchment analysis remains a separate step.
Keep in mind: Area statistics are not an individual's income or creditworthiness. rastr supplies no credit scores, hazard layers, automated lending decisions or regulatory compliance assessments.
Geo analytics
Your analysis starts with addresses, while your GIS, notebook or dashboard needs coordinates and comparable demographic fields.
How rastr helps
Use forward or reverse geocoding with census enrichment to connect German locations to demographic context through the API. Bring coordinates, population, age bands and available data-period information into your own pipeline.
A practical workflow
Enrich store locations through the API and visualise their residential context in your GIS or BI tool. Compare locations using the same dataset period, and handle missing values explicitly.
Keep in mind: Multiple addresses can share one cell. Deduplicate cells before aggregating populations; adding every address result would count the same residents more than once. rastr does not measure footfall or actual audiences.
Utilities & telecom
Expansion planning needs both a geographic view of service locations and an understanding of the residential areas around them.
How rastr helps
Locate service addresses and attach population, age structure and household context. Use these as supporting inputs when comparing German service or rollout areas against your own network and coverage data.
A practical workflow
Map candidate fibre rollout locations, then compare residential context alongside your own coverage, connection costs and demand evidence. Use the results to inform further investigation, not as a network plan.
Keep in mind: Population is not a count of connections or subscribers. rastr does not provide broadband availability, meter matching, energy consumption, heat-demand models or network engineering.
One foundation, different applications.
Start with a location
Look up a German address or coordinates in the dashboard or through the API.
Place it on the map
Receive coordinates and an address result with its geocoding granularity.
Add demographic context
Retrieve available statistics for the associated 100 × 100 m grid cell, with data-period information.
Use your own tools
Combine the results with your own data and models in your application, GIS or BI workflow.
Know what the data describes.
Demographics describe the residential population of the address-associated 100 × 100 m grid cell — not an individual, a building or a measured catchment. Rooftop geocoding does not make demographic figures building-level data.
Census 2022 is the official baseline. Where available, modeled updates use official inputs but are estimates, not new observations of every cell. Compare data periods and provenance before drawing conclusions.
Unpublished or suppressed values remain missing, not zero. Germany-only coverage and the limitations of your own downstream analysis still apply.
Explore data and methodologyStart with a location you know.
Inspect an address result, integrate the API, or discuss a small spreadsheet pilot for your use case.
Address lookup requires an account. The free pilot includes one manually prepared CSV with up to 20 addresses per organisation. Self-service list upload and spreadsheet export are not yet available.