The Allegheny County Health Department has generated this list of fast food restaurants by exporting all chain restaurants without an alcohol permit from the County’s Fee and Permit System. A chain restaurant defined by the County is any restaurant that has more than one location in the County. Chain restaurants capture both local and national chains (including locally owned national chains) so long as there is one or more establishments in operation within the County.

Xavvy fuel is the leading source for location data and market insights worldwide. We specialize in data quality and enrichment, providing high-quality POI data for restaurants and quick-service establishments in the United States.

Base data • Name/Brand • Adress • Geocoordinates • Opening Hours • Phone • ... ^

30+ Services • Delivery • Wifi • ChargePoints • …

10+ Payment options • Visa • MasterCard • Google Pay • individual Apps • ...

Our data offering is highly customizable and flexible in delivery – whether one-time or regular data delivery, push or pull services, and various data formats – we adapt to our customers' needs.

Brands included: • McDonalds • Burger King • Subway • KFC • Wendy's • ...

The total number of restaurants per region, market share distribution among competitors, or the ideal location for new branches – our restaurant data provides valuable insights into the food service market and serves as the perfect foundation for in-depth analyses and statistics. Our data helps businesses across various industries make informed decisions regarding market development, expansion, and competitive strategies. Additionally, our data contributes to the consistency and quality of existing datasets. A simple data mapping allows for accuracy verification and correction of erroneous entries.

Especially when displaying information about restaurants and fast-food chains on maps or in applications, high data quality is crucial for an optimal customer experience. Therefore, we continuously optimize our data processing procedures: • Regular quality controls • Geocoding systems to refine location data • Cleaning and standardization of datasets • Consideration of current developments and mergers • Continuous expansion and cross-checking of various data sources

Integrate the most comprehensive database of restaurant locations in the USA into your business. Explore our additional data offerings and gain valuable market insights directly from the experts!

Context

This is a list of 10,000 fast-food restaurants provided by Datafiniti's Business Database. The dataset includes the restaurant's address, city, latitude and longitude coordinates, name, and more.

Inspiration

You can use this data to rank cities with the most and least fast-food restaurants across the U.S. E.g.:

1. Cities with the most and least McDonald's per capita
2. Fast food restaurants per capita for all states
3. Fast food restaurants with the most locations nationally
4. Major cities with the most and least fast food restaurants per capita
5. Small cities with the most fast-food restaurants per capita
6. States with the most and least fast food restaurants per capita
7. The number of fast-food restaurants per capita

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Comprehensive dataset of 367,275 Fast food restaurants in India as of August, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

According to a survey on fast food conducted in Indonesia in February 2023, around ** percent of respondents stated that they ate fast food once a week. In comparison, *** percent of respondents said that they ate fast food more than ***** times a week.

Xtract.io's comprehensive McDonald's location data provides a detailed view of the global fast-food chain's network. Restaurant investors, market researchers, and business analysts can utilize this dataset to analyze market penetration, identify expansion opportunities, and develop a sophisticated understanding of McDonald's geographical strategy.

Point of Interest (POI) data, also known as places data, provides the exact location of buildings, stores, or specific places. It has become essential for businesses to make smarter, geography-driven decisions in today's competitive landscape.

LocationsXYZ, the POI data product from Xtract.io, offers a comprehensive database of 6 million locations across the US, UK, and Canada, spanning 11 diverse industries, including:

-Retail -Restaurants -Healthcare -Automotive -Public utilities (e.g., ATMs, park-and-ride locations) -Shopping malls, and more

Why Choose LocationsXYZ? At LocationsXYZ, we: -Deliver POI data with 95% accuracy -Refresh POIs every 30, 60, or 90 days to ensure the most recent information -Create on-demand POI datasets tailored to your specific needs -Handcraft boundaries (geofences) for locations to enhance accuracy -Provide POI and polygon data in multiple file formats

Unlock the Power of POI Data With our point-of-interest data, you can: -Perform thorough market analyses -Identify the best locations for new stores -Gain insights into consumer behavior -Achieve an edge with competitive intelligence

LocationsXYZ has empowered businesses with geospatial insights, helping them scale and make informed decisions. Join our growing list of satisfied customers and unlock your business's potential with our cutting-edge POI data.

China Chain: Fast Food: Number of Store data was reported at 29,221.000 Unit in 2023. This records an increase from the previous number of 25,205.000 Unit for 2022. China Chain: Fast Food: Number of Store data is updated yearly, averaging 11,892.000 Unit from Dec 2003 (Median) to 2023, with 21 observations. The data reached an all-time high of 29,221.000 Unit in 2023 and a record low of 1,966.000 Unit in 2003. China Chain: Fast Food: Number of Store data remains active status in CEIC and is reported by Ministry of Commerce, China General Chamber of Commerce. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.CCAC: Fast Food.

1) Data Introduction • The Fast Food Classification Dataset is designed for image classification of various fast food items, consisting of a total of 10 classes: Burger, Donut, Hot Dog, Pizza, Sandwich, Baked Potato, Crispy Chicken, Fries, Taco, and Taquito.

2) Data Utilization (1) Characteristics of the Fast Food Classification Dataset: • The dataset includes images captured under various lighting conditions, backgrounds, and angles, making it suitable for evaluating the generalization performance of classification models in real-world scenarios.

(2) Applications of the Fast Food Classification Dataset: • Training fast food image classification models: Can be used to develop deep learning–based image classifiers that accurately distinguish between various fast food items. • Building automated food recognition systems: Applicable to real-time food identification and classification in self-order kiosks, smart POS systems, and food recognition apps.

The Johns Hopkins Center for a Livable Future (CLF) obtained the food permit list from the Baltimore City Health Department in August 2011, which includes all sites that sell food, such as stores, restaurants and temporary locations such as farmers' market stands and street carts. The restaurants were grouped into three categories, including full service restaurants, fast food chains and carryouts. Carryout and fast food chain restaurants were extracted from the restaurant layer and spatially joined with the 2010 Community Statistical Area (CSA) data layer, provided by BNIA-JFI. The prepared foods density, per 1,000 people, was calculated for each CSA using the CSA's population and the total number of carryout and fast food restaurants, including vendors selling prepared foods in public markets, in each CSA. Source: Johns Hopkins University, Center for a Livable FutureYears Available: 2011, 2013, 2018, 2019

Detailed POI data for all McDonald's locations in US and Canada. Enables in-depth analysis of the fast-food industry's market leader, supporting competitive intelligence and market penetration studies.

Jilin: Chain: Fast Food: Number of Store data was reported at 14.000 Unit in 2010. This records an increase from the previous number of 12.000 Unit for 2009. Jilin: Chain: Fast Food: Number of Store data is updated yearly, averaging 12.000 Unit from Dec 2005 (Median) to 2010, with 3 observations. The data reached an all-time high of 14.000 Unit in 2010 and a record low of 7.000 Unit in 2005. Jilin: Chain: Fast Food: Number of Store data remains active status in CEIC and is reported by Ministry of Commerce, China General Chamber of Commerce. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.CCAC: Fast Food: Jilin.

Comprehensive dataset of 20,874 Fast food restaurants in Germany as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

China Chain: Fast Food: Operating Area data was reported at 7,440.000 sq m th in 2023. This records an increase from the previous number of 6,566.973 sq m th for 2022. China Chain: Fast Food: Operating Area data is updated yearly, averaging 3,697.838 sq m th from Dec 2003 (Median) to 2023, with 21 observations. The data reached an all-time high of 7,440.000 sq m th in 2023 and a record low of 1,006.595 sq m th in 2004. China Chain: Fast Food: Operating Area data remains active status in CEIC and is reported by Ministry of Commerce, China General Chamber of Commerce. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.CCAC: Fast Food.

Geospatial data about Fast food restaurants (% change), 2007 12. Export to CAD, GIS, PDF, CSV and access via API.

Potential Applications of the Dataset:

1. Geospatial Information: Precise geographical coordinates for each Walgreens store, enabling accurate mapping and spatial analysis. State-wise and city-wise breakdown of store locations for a comprehensive overview.

2. Store Details: Store addresses, including street name, city, state, and zip code, facilitating easy identification and location-based analysis. Contact information, such as phone numbers, providing a direct link to store management.

3. Operational Attributes: Store opening and closing hours, aiding businesses in strategic planning and market analysis. Services and amenities are available at each location, offering insights into the diverse offerings of Walgreens stores.

4. Historical Data: Historical data on store openings and closures, providing a timeline perspective on Walgreens' expansion and market presence.

5. Demographic Insights: Demographic information of the areas surrounding each store, empowering users to understand the local customer base.

6. Comprehensive and Up-to-Date: Regularly updated to ensure the dataset reflects the latest information on Walgreens store locations and attributes. Detailed data quality checks and verification processes for accuracy and reliability.

The dataset is structured in a flexible format, allowing users to tailor their queries and analyses based on specific criteria and preferences.

China Chain: Fast Food: Purchase data was reported at 48.630 RMB bn in 2023. This records an increase from the previous number of 38.302 RMB bn for 2022. China Chain: Fast Food: Purchase data is updated yearly, averaging 33.506 RMB bn from Dec 2005 (Median) to 2023, with 19 observations. The data reached an all-time high of 48.630 RMB bn in 2023 and a record low of 6.928 RMB bn in 2005. China Chain: Fast Food: Purchase data remains active status in CEIC and is reported by Ministry of Commerce, China General Chamber of Commerce. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.CCAC: Fast Food.

China Chain: Fast Food: Business Revenue data was reported at 150.120 RMB bn in 2023. This records an increase from the previous number of 121.256 RMB bn for 2022. China Chain: Fast Food: Business Revenue data is updated yearly, averaging 80.409 RMB bn from Dec 2003 (Median) to 2023, with 21 observations. The data reached an all-time high of 150.120 RMB bn in 2023 and a record low of 10.848 RMB bn in 2003. China Chain: Fast Food: Business Revenue data remains active status in CEIC and is reported by Ministry of Commerce, China General Chamber of Commerce. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.CCAC: Fast Food.

Snapshot img

Fast Food Market Size and Forecast 2025-2029

The fast food market size estimates the market to reach by USD 119.6 billion, at a CAGR of 3% between 2024 and 2029. APAC is expected to account for 35% of the growth contribution to the global market during this period. In 2019 the non-vegetarian fast food segment was valued at USD 424.90 billion and has demonstrated steady growth since then.

    Report Coverage


    Details




    Base year


    2024




    Historic period

    2019-2023



    Forecast period


    2025-2029



    Market structure
    Fragmented



    Market growth 2025-2029


    USD 119.6 billion






The market is experiencing significant shifts, driven by the increasing online presence of companies and the proliferation of new outlets. This digital transformation allows fast food companies to expand their reach and engage customers through various digital channels, offering convenience and personalized experiences. Simultaneously, the market faces challenges due to growing health concerns surrounding the excessive consumption of fast foods. As more consumers prioritize wellness and balanced diets, fast food companies must respond by offering healthier options and transparent nutritional information.
The growing number of fast-food outlets intensifies competition, necessitating innovative marketing strategies and operational efficiencies to maintain market share. Companies that successfully navigate these trends and challenges will capitalize on the market's potential for growth and customer loyalty.

What will be the Size of the Fast Food Market during the forecast period?

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The global food service equipment market is advancing as operators adopt restaurant technology that enhances pos terminal integration, online ordering integration, and kitchen workflow efficiency. Businesses are combining employee training programs with data driven decision making to improve operational efficiency while ensuring compliance with strict sanitation protocols and food quality control standards. The integration of supply chain traceability tools supports transparency, enabling faster issue resolution and improved inventory control.

Market adoption has risen by 21.8% as restaurants focus on cost reduction strategies without compromising customer experience. Forward-looking expectations project a 28.6% improvement in profitability for operators that successfully align menu optimization, quality assurance, and food cost control with advanced analytics. This reflects a shift toward using marketing analytics to strengthen brand positioning, increasing both customer acquisition and customer retention rates.

Comparing recent performance metrics, establishments that implemented customer feedback systems and sales forecasting tools achieved a 7.4% higher revenue growth rate than those using manual store operations processes. Furthermore, well-executed franchise development, combined with strategic location analysis and effective staff management, has shown measurable gains in revenue generation and long-term profitability analysis. By integrating risk management frameworks with evolving technologies, businesses are positioned to sustain growth and protect market share while continuously refining the customer experience.

How is this Fast Food Industry segmented?

The fast food industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Non-vegetarian fast food
  Vegetarian fast food


Service Type

  Eat-in
  Take away
  Home delivery
  Others


End-User

  Quick Service Restaurants
  Fast Casual Restaurants
  Others


Target Audience

  Youth
  Families
  Professionals


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    Italy
    Spain
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Product Insights

The non-vegetarian fast food segment is estimated to witness significant growth during the forecast period.

In the dynamic the market, various players prioritize customer feedback systems and menu engineering to cater to evolving consumer preferences. Menu offerings emphasize non-vegetarian items, with fish, seafood, chicken, beef, and others in high demand due to their appetizing nature. The preparation techniques and modes of service differ from restaurant to restaurant, encouraging consumers to explore diverse non-vegetarian options. The market's growth is further influenced by the demand for low-calorie, high-protein food p

Comprehensive dataset of 44,880 Fast food restaurants in France as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

The market size of the United Kingdom's fast food and takeaway industry stood at **** billion British pounds in 2025. Meanwhile, employees in the sector numbered over *******. How many fast food and takeaway restaurants are in the UK? The number of businesses in the UK's takeaway and fast food sector totaled close to ****** as of April 2025. At the forefront of the industry are household names such as Greggs, KFC, and McDonald's, all of which regularly rank among the most popular dining brands in the UK. Greggs, in particular, has seen impressive growth in the past two decades, with the bakery chain's turnover more than tripling between 2006 and 2023. What is the most popular takeaway food in Great Britain? A 2023 survey asked consumers in Great Britain to rank their favorite type of takeaway food. ***** ended up being the most popular takeaway cuisine in Great Britain that year, with ** percent of respondents choosing the dish. Other popular takeaway options in the United Kingdom’s restaurant delivery and takeaway industry include Chinese, Italian, and Burgers.