SPAR Supermarket Locations Dataset – Hungary

SPAR is a major player in the Hungarian grocery sector, operating a diverse range of formats from small convenience stores to large INTERSPAR hypermarkets. It is well-regarded for its high-quality meat and deli departments, often sourced from its own regional production sites.

There are 658 SPAR Supermarkets as of 29 May 2026 in Hungary. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all SPAR locations, including full address details, administrative divisions, and precise WGS84 latitude/longitude coordinates - structured for GIS, retail analytics, mapping, and AI/RAG workflows.

Dataset Methodology:

This dataset is compiled from publicly available business listings, official company sources, and geospatial validation workflows. Automated quality checks and manual analyst reviews are applied to improve coordinate precision, address standardisation, duplicate detection, and overall analytical consistency.

It is periodically reviewed and updated to reflect known network changes, closures, relocations, and newly identified locations.

Data Quality Scorecard

Data Preview: Sample geospatial records from the SPAR dataset in Hungary

ID	Location Title	Latitude	Longitude	Postal Code	Full Address
094a79e...	SPAR partner (Taksony)	47.335389	19.065533	2335	10 Szent István tér, Taksony, 2335, H...
96c40e7...	SPAR (IV. kerület)	47.586775	19.112653	1048	12 Kordován tér, Budapest, 1048, Hungary
3ead925...	SPAR market (Zomba)	46.411534	18.565572	7173	2 Rákóczi utca, Zomba, 7173, Hungary
09d4871...	SPAR (XVIII. kerület)	47.433024	19.178258	1182	15/b Cziffra György utca, Budapest, 1...
98d4d7f...	DESPAR (Tárnok)	47.356661	18.809052	2461	M7, Tárnok, 2461, Hungary

Note: Only a subset of the full dataset fields are displayed here. Download the free sample (option above) to view all fields and verify the data structure.

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Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of SPAR locations in Hungary is found in Közép-Magyarország (255 sites, equivalent to 8.44 SPAR supermarkets per 100,000 residents). This is followed by Közép-Dunántúl (89 sites; 8.48 per 100,000) and Nyugat-Dunántúl (78 sites; 8.04 per 100,000). From a market-penetration perspective, Közép-Dunántúl has the highest brand density at 8.48 locations per 100,000 people (population: 1,050,000), making it the most saturated region for SPAR in Hungary. By contrast, Észak-Alföld records only 4.1 locations per 100,000 residents (population: 1,390,000), indicating a potential white-space opportunity for network expansion or competitor analysis.

Also available for Hungary

Related geospatial datasets

• Administrative boundaries and full polygon dataset for Hungary: Map these SPAR locations against highly precise administrative polygons for territory analysis and spatial structuring.
• Demographics dataset for Hungary: Overlay demographic indicators to deeply understand the population structures and household types surrounding these SPAR locations.
• Explore demographics data insights for Hungary: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
• Income indicators dataset for Hungary (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.
• Income distribution and socio-economic patterns in Hungary - expert analysis: A detailed blog post explaining income geography, disparities, and how income-based indicators can support location intelligence and market analytics.
• Explore a rich library of Hungary-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 Hungary

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 contact@geolocet.com.

Who uses this data?

• Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
• Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
• B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
• Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
• Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
• Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
• Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.

Frequently Asked Questions

Analyze this data with AI

Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:

• "Analyze this SPAR dataset to identify underserved regions in Hungary for potential market expansion."
• "Identify fast-growing suburban areas in Hungary that currently have limited access to nearby supermarkets."
• "Identify regions in Hungary where SPAR has a disproportionately strong or weak presence relative to population density."

Disclaimer: All brand logos and trademarks displayed are the property of their respective owners and are used strictly for identification purposes. This product consists of geospatial location data only; no images, logos, or trademark rights are included in the downloadable files.