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Description
Germany Grocery Locations Dataset – Top 27 Supermarket BrandsQuick links: Overview Dataset Fields Brand Distribution Distribution by Federal State Download FAQ Analyze with AI Top 27 Supermarket Chains Across Germany: Premium Multi Brand Location Dataset Unlock a complete, ready to use dataset featuring the leading Supermarket brands in Germany. This expertly compiled Top Brands dataset consolidates all major Supermarket chains in Germany, delivering a clean, standardised and analysis ready collection of 32,138
Top 27 Supermarket Chains Across Germany: Premium Multi-Brand Location Dataset
Unlock a complete, ready-to-use dataset featuring the leading Supermarket brands in Germany. This expertly compiled Top Brands dataset consolidates all major Supermarket chains in Germany, delivering a clean, standardised and analysis-ready collection of 32,138 locations. Perfect for businesses seeking high-quality data for market sizing, competitive landscape analysis, network optimisation, and strategic planning.
Last updated: 27 May 2026.
Dataset fields included in the CSV:
- GUID
- Title
- Latitude
- Longitude
- Street No
- Street
- Area
- City
- Admin_level_1
- Admin_level_2
- Gemainde
- Federal State
- Population
- Postal Code
- Address
- Wheelchair
- Popularity Score
- Phone
- Website
- Opening hours
Brand distribution
- ALDI – 4,329 locations in Germany
- Alnatura – 131 locations in Germany
- Combi – 205 locations in Germany
- Denns BioMarkt – 317 locations in Germany
- EDEKA – 6,469 locations in Germany
- EuroShop – 287 locations in Germany
- famila – 179 locations in Germany
- FRISTO – 206 locations in Germany
- GLOBUS – 85 locations in Germany
- HIT – 104 locations in Germany
- HOL'AB! – 159 locations in Germany
- K + K Klaas – 199 locations in Germany
- Kaufland – 821 locations in Germany
- Konsum – 124 locations in Germany
- Lidl – 3,322 locations in Germany
- METRO – 95 locations in Germany
- Mix Markt – 199 locations in Germany
- MÄC-GEIZ – 190 locations in Germany
- Nahkauf – 547 locations in Germany
- Netto – 4,765 locations in Germany
- Norma – 1,371 locations in Germany
- NP-Markt – 195 locations in Germany
- PENNY – 2,163 locations in Germany
- REWE – 5,014 locations in Germany
- SPAR – 289 locations in Germany
- Tante-M – 74 locations in Germany
- tegut... – 299 locations in Germany
Supermarkets distribution by Federal State
- Nordrhein-Westfalen: 5,937 supermarkets
- Bayern: 5,518 supermarkets
- Baden-Württemberg: 3,863 supermarkets
- Niedersachsen: 3,469 supermarkets
- Hessen: 2,454 supermarkets
- Sachsen: 1,803 supermarkets
- Rheinland-Pfalz: 1,488 supermarkets
- Schleswig-Holstein: 1,262 supermarkets
- Sachsen-Anhalt: 1,161 supermarkets
- Brandenburg: 1,156 supermarkets
- Berlin: 1,048 supermarkets
- Thüringen: 923 supermarkets
- Mecklenburg-Vorpommern: 873 supermarkets
- Hamburg: 581 supermarkets
- Saarland: 359 supermarkets
- Bremen: 243 supermarkets
Direct access after purchase of the complete locations dataset for Germany
Download the dataset immediately in a clean, analysis-ready CSV format. Ideal for geospatial analysis, competitor benchmarking, market studies, site planning, and retail location intelligence workflows.
Evaluate the dataset before purchase
A free sample is available for download, allowing you to inspect the structure, fields, and geospatial precision before purchasing the full dataset.
Related geospatial datasets
- Administrative boundaries and full polygon dataset for Germany: Map these supermarkets locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Germany: Overlay demographic indicators to deeply understand the population structures and household types surrounding these supermarkets locations.
- Explore demographics data insights for Germany: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Income indicators dataset for Germany (small-area income analysis): Download an analysis-ready dataset on income distribution across small geographic units - ideal for segmentation, customer analytics, location planning, and socio-economic scoring.
- Explore a rich library of Germany-specific datasets on our dedicated country page: detailed demographics, wealth indicators, multi-level boundaries, and a broad spectrum of retail POIs. View demographics, retail POI, and administrative boundary datasets for Germany
Need the data in another format?
We can deliver this dataset in alternative formats upon request (GeoJSON, Shapefile, Excel, PostgreSQL import files, etc.). Contact us at [email protected].
Frequently Asked Questions
Q: Can this dataset be used for logistics planning?
A: Yes. Many customers use these datasets to optimize delivery territories, distribution networks, route planning, and last-mile logistics analysis.
Q: Can I integrate this dataset into a PostgreSQL/PostGIS database?
A: Yes. The dataset structure is compatible with PostgreSQL/PostGIS and other relational spatial databases.
Q: Can I use this dataset for proximity analysis?
A: Yes. The geocoded coordinates are suitable for drive-time analysis, catchment modeling, nearest-neighbor analysis, and accessibility studies.
Q: Can this dataset be imported into Power BI or Tableau?
A: Yes. The CSV structure is compatible with Power BI, Tableau, Looker Studio, and other business intelligence platforms.
Q: Can this dataset support territory optimization?
A: Yes. The dataset is suitable for defining service territories, balancing regional coverage, and optimizing operational footprints.
Q: Does the dataset include opening hours?
A: Yes, opening hours are included where publicly available and validated during the data standardization process.
Q: Does the dataset include latitude and longitude coordinates?
A: Yes. Each location record includes precise WGS84 latitude and longitude coordinates for geospatial analysis and mapping workflows.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this this multi-brand dataset to identify underserved regions in Germany for potential market expansion.""Identify regions in Germany where this multi-brand has a disproportionately strong or weak presence relative to population density.""Identify isolated this multi-brand sites in Germany that may face operational inefficiencies due to low regional clustering."
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