15 datasets found
  1. Market share of mobile operating systems worldwide 2009-2025, by quarter

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Market share of mobile operating systems worldwide 2009-2025, by quarter [Dataset]. https://www.statista.com/statistics/272698/global-market-share-held-by-mobile-operating-systems-since-2009/
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Android maintained its position as the leading mobile operating system worldwide in the first quarter of 2025 with a market share of about ***** percent. Android's closest rival, Apple's iOS, had a market share of approximately ***** percent during the same period. The leading mobile operating systems Both unveiled in 2007, Google’s Android and Apple’s iOS have evolved through incremental updates introducing new features and capabilities. The latest version of iOS, iOS 18, was released in September 2024, while the most recent Android iteration, Android 15, was made available in September 2023. A key difference between the two systems concerns hardware - iOS is only available on Apple devices, whereas Android ships with devices from a range of manufacturers such as Samsung, Google and OnePlus. In addition, Apple has had far greater success in bringing its users up to date. As of February 2024, ** percent of iOS users had iOS 17 installed, while in the same month only ** percent of Android users ran the latest version. The rise of the smartphone From around 2010, the touchscreen smartphone revolution had a major impact on sales of basic feature phones, as the sales of smartphones increased from *** million units in 2008 to **** billion units in 2023. In 2020, smartphone sales decreased to **** billion units due to the coronavirus (COVID-19) pandemic. Apple, Samsung, and lately also Xiaomi, were the big winners in this shift towards smartphones, with BlackBerry and Nokia among those unable to capitalize.

  2. Smartphones Sales Dataset

    • kaggle.com
    Updated Mar 3, 2024
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    Yamin Hossain (2024). Smartphones Sales Dataset [Dataset]. https://www.kaggle.com/datasets/yaminh/smartphone-sale-dataset
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 3, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Yamin Hossain
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Description for each of the variables:

    1. Brands: The brands of smartphones included in the dataset.
    2. Colors: The colors available for the smartphones.
    3. Memory: The storage capacity of the smartphones, typically measured in gigabytes (GB) or megabytes (MB).
    4. Storage: The internal storage capacity of the smartphones, often measured in gigabytes (GB) or megabytes (MB).
    5. Rating: The user ratings or scores assigned to the smartphones, reflecting user satisfaction or performance.
    6. Selling Price: The price at which the smartphones are sold to consumers.
    7. Original Price: The original or list price of the smartphones before any discounts or promotions.
    8. Mobile: Indicates whether the device is a mobile phone.
    9. Discount: The discount applied to the original price to calculate the selling price.
    10. Discount percentage: The percentage discount applied to the original price to calculate the selling price.
  3. Number of smartphone users in the United States 2014-2029

    • statista.com
    Updated May 5, 2025
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    Statista Research Department (2025). Number of smartphone users in the United States 2014-2029 [Dataset]. https://www.statista.com/topics/2711/us-smartphone-market/
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    Dataset updated
    May 5, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    United States
    Description

    The number of smartphone users in the United States was forecast to continuously increase between 2024 and 2029 by in total 17.4 million users (+5.61 percent). After the fifteenth consecutive increasing year, the smartphone user base is estimated to reach 327.54 million users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of smartphone users in countries like Mexico and Canada.

  4. d

    Mobile App Usage | 1st Party | 3B+ events verified, US consumers |...

    • datarade.ai
    • omnitrafficdata.mfour.com
    .csv, .parquet
    Updated Dec 13, 2021
    + more versions
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    MFour (2021). Mobile App Usage | 1st Party | 3B+ events verified, US consumers | Event-level iOS & Android [Dataset]. https://datarade.ai/data-products/mobile-app-usage-1st-party-3b-events-verified-us-consum-mfour
    Explore at:
    .csv, .parquetAvailable download formats
    Dataset updated
    Dec 13, 2021
    Dataset authored and provided by
    MFour
    Area covered
    United States of America
    Description

    This dataset encompasses mobile smartphone application (app) usage, collected from over 150,000 triple-opt-in first-party US Daily Active Users (DAU). Use it for measurement, attribution or surveying to understand the why. iOS and Android operating system coverage.

    Tie app usage to web and location events using anonymized PanelistID for omnichannel consumer journey understanding.

  5. 📱Smartphone Processors Ranking & Scores📊

    • kaggle.com
    Updated Jan 31, 2023
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    Alan Jo (2023). 📱Smartphone Processors Ranking & Scores📊 [Dataset]. https://www.kaggle.com/datasets/alanjo/smartphone-processors-ranking
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 31, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Alan Jo
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Welcome to the ultimate Android vs iOS battle with this Smartphone SoC dataset!

    Includes three .csv files. Any analysis is appreciated, even if it is a short one 😎

    Context

    Benchmarks allow for easy comparison between multiple devices by scoring their performance on a standardized series of tests, and they are useful in many instances: When buying a new phone or tablet

    Content

    smartphone cpu_stats.csv is the main data. Updated performance rating of smartphone SoCs as of 2022. Includes summary of Geekbench 5 and AnTuTu v9 scores. Includes CPU specs such as clock speed, core count, core config, and GPU.

    ML ALL_benchmarks.csv is the Geekbench ML Benchmark data. This tells you how well each smartphone device performs when performing Machine Learning tasks. The data is gathered from user-submitted Geekbench ML results from the Geekbench Browser. To make sure the results accurately reflect the average performance of each device, the dataset only includes devices with at least five unique results in the Geekbench Browser.

    antutu android vs ios_v4.csv is the AnTuTu benchmarks data. It includes information about CPU, GPU, MEM, UX and Total score.

    Antutu Benchmarks

    1. Total Score

    Benchmark apps gives your device an overall numerical score as well as individual scores for each test it performs. The overall score is created by adding the results of those individual scores. These score numbers don't mean much on their own, they're just helpful for comparing different devices. For example, if your device's score is 300000, a device with a score of 600000 is about twice as fast. You can use individual test scores to compare the relative performance of specific parts of different devices. For example, you could compare how fast your phone's storage performs compared to another phone's storage.

    2. CPU Score

    The first part of the overall score is your CPU score. The CPU score in turn includes the output of CPU Mathematical Operations, CPU Common Algorithms, and CPU Multi-Core. In simpler words, the CPU score means how fast your phone processes commands. Your device's central processing unit (CPU) does most of the number-crunching. A faster CPU can run apps faster, so everything on your device will seem faster. Of course, once you get to a certain point, CPU speed won't affect performance much. However, a faster CPU may still help when running more demanding applications, such as high-end games.

    3. GPU Score

    The second part of the overall score is your GPU score. This score is comprised of the output of graphical components like Metal, OpenGL or Vulkan, depending on your device. The GPU score means how well your phone displays 2D and 3D graphics. Your device's graphics processing unit (GPU) handles accelerated graphics. When you play a game, your GPU kicks into gear and renders the 3D graphics or accelerates the shiny 2D graphics. Many interface animations and other transitions also use the GPU. The GPU is optimized for these sorts of graphics operations. The CPU could perform them, but it's more general-purpose and would take more time and battery power. You can say that your GPU does the graphics number-crunching, so a higher score here is better.

    4. MEM score

    The third part of the overall score is your MEM score. The MEM score includes the results of the output of RAM Access, ROM APP IO, ROM Sequential Read and Write, and ROM Random Access. In simpler words, the MEM score means how fast and how much memory your phone possesses. RAM stands for random-access memory; while ROM stands for read-only memory. Your device uses RAM as working memory, while flash storage or an internal SD card is used for long-term storage. The faster it can write to and read data from its RAM, the faster your device will perform. Your RAM is constantly being used on your device, whatever you're doing. While RAM is volatile in nature, ROM is its opposite. RAM mostly stores temporary data, while ROM is used to store permanent data like the firmware of your phone. Both the RAM and ROM make up the memory of your phone, helping it to perform tasks efficiently.

    5. UX Score

    The fourth and final part of the overall score is your UX score. The UX score is made up of the results of the output of the Data Security, Data Processing, Image Processing, User Experience, and Video CTS and Decode tests. The UX score means an overall score that represents how the device's "user experience" will be in the real world. It's a number you can look at to get a feel for a device's overall performance without digging into the above benchmarks or relying too much on the overall score.

    Acknowledgements

    Sourced from Geekbench and AnTuTu.

    If you enjoyed this dataset, here's some similar datasets you may like 😎

  6. m

    Mobile Web Clickstream | 1st Party | 3B+ events verified, US consumers |...

    • omnitrafficdata.mfour.com
    • datarade.ai
    Updated Aug 1, 2021
    + more versions
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    MFour (2021). Mobile Web Clickstream | 1st Party | 3B+ events verified, US consumers | Safari, Chrome, any iOS or Android [Dataset]. https://omnitrafficdata.mfour.com/products/mobile-web-clickstream-1st-party-3b-events-verified-us-mfour
    Explore at:
    Dataset updated
    Aug 1, 2021
    Dataset authored and provided by
    MFour
    Area covered
    United States
    Description

    This dataset encompasses mobile web clickstream behavior on any browser, collected from over 150,000 triple-opt-in first-party US Daily Active Users (DAU). Use it for measurement, attribution or path to purchase and consumer journey understanding. Full URL deliverable available including searches.

  7. Mobile Games (Android and IOS) Rating Dataset

    • kaggle.com
    Updated May 25, 2024
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    Amaan Patel (2024). Mobile Games (Android and IOS) Rating Dataset [Dataset]. https://www.kaggle.com/datasets/dem0nking/mobile-games-android-and-ios-rating-dataset/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 25, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Amaan Patel
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    The Mobile Games Dataset is a meticulously curated collection of 100+ top-rated mobile games spanning various genres. This dataset provides a valuable resource for game developers, researchers, and enthusiasts interested in exploring trends and patterns within the mobile gaming industry. Each entry includes the game name, developer, genre, and rating, offering a comprehensive overview of some of the most popular and critically acclaimed mobile games available today.

    Column Descriptions:

    • Game Name: The title of the mobile game.

      • Type: String
      • Example: "Candy Crush Saga"
    • Developer: The name of the company or individual who developed the game.

      • Type: String
      • Example: "King"
    • Genre: The category or type of game, indicating the primary gameplay mechanics.

      • Type: String
      • Example: "Puzzle"
    • Rating: The average user rating of the game, typically on a scale from 1 to 5.

      • Type: Float
      • Example: 4.6
  8. Pegasus Spyware Attack(Synthetic Dataset)

    • kaggle.com
    Updated Aug 1, 2024
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    Krishna1502 (2024). Pegasus Spyware Attack(Synthetic Dataset) [Dataset]. https://www.kaggle.com/datasets/krishna1502/pegasus-spyware-attacksynthetic-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 1, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Krishna1502
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    This dataset contains synthetic logs designed to simulate the activity of the Pegasus malware, providing a rich resource for cybersecurity research, anomaly detection, and machine learning applications. The dataset includes 1000 entries with 17 columns, each capturing detailed information about device usage, network traffic, and potential security events

    Columns: user_id: Unique identifier for each user device_type: Type of device used (e.g., iPhone, Android) os_version: Operating system version of the device app_usage_pattern: Usage pattern of the applications (Low, Normal, High) timestamp: Timestamp of the recorded activity source_ip: Source IP address of the network traffic destination_ip: Destination IP address of the network traffic protocol: Network protocol used (e.g., HTTPS, FTP, SSH) data_volume: Volume of data transferred in the session log_type: Type of log entry (system, application, security) event: Specific event type (e.g., App Install, System Update, Logout, App Crash) event_description: Description of the event error_code: Error code associated with the event file_accessed: File path accessed during the event process: Process name involved in the event anomaly_detected: Description of any detected anomalies (e.g., Unknown Process Execution, Suspicious File Access) ioc: Indicators of Compromise (e.g., Pegasus Signature, Known Malicious IP)

    This dataset is ideal for those looking to develop and test cybersecurity solutions, understand malware behavior, or create educational tools for cybersecurity training. The data captures various scenarios of potential malware activities, making it a versatile resource for a range of cybersecurity applications.

  9. h

    vcard-to-csv-converter

    • huggingface.co
    Updated May 29, 2025
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    twinkle lawrence (2025). vcard-to-csv-converter [Dataset]. https://huggingface.co/datasets/lawrwtwinkle111/vcard-to-csv-converter
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    Dataset updated
    May 29, 2025
    Authors
    twinkle lawrence
    Description

    Want to save VCF files in Excel? Then try CubexSoft vCard to CSV Converter Tool. The tool helps to change format of multiple VCF files into CSV files at once. Also, it is easy very simple to understand this tool’s functions, without requiring any tech-skill. The app is eligible to convert vCard from Android, Apple Phone, Computer, Smartphone, etc. Users can launch this VCF to CSV Tool on Windows Operating Systems. And for demo purpose, it let users to change 5 .vcf files to .csv files free of… See the full description on the dataset page: https://huggingface.co/datasets/lawrwtwinkle111/vcard-to-csv-converter.

  10. Data from: Sightings Map of Invasive Plants in Portugal

    • gbif.org
    • demo.gbif.org
    Updated Jan 20, 2021
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    Hélia Marchante; Maria Cristina Morais; Hélia Marchante; Maria Cristina Morais (2021). Sightings Map of Invasive Plants in Portugal [Dataset]. http://doi.org/10.15468/ic8tid
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    Dataset updated
    Jan 20, 2021
    Dataset provided by
    Global Biodiversity Information Facilityhttps://www.gbif.org/
    CFE - Centre for Functional Ecology, Department of Life Sciences, University of Coimbra
    Authors
    Hélia Marchante; Maria Cristina Morais; Hélia Marchante; Maria Cristina Morais
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Feb 22, 2013 - Feb 15, 2020
    Area covered
    Description

    The dataset available through the Sightings Map of Invasive Plants in Portugal results from the Citizen Science platform INVASORAS.PT, which records sightings of invasive plants in Portugal (mainland and Archipelagos of Madeira and Azores). This platform was originally created in 2013, in the context of the project “Plantas Invasoras: uma ameaça vinda de fora” (Media Ciência nº 16905), developed by researchers from Centre for Functional Ecology of University of Coimbra and of Coimbra College of Agriculture of the Polytechnic Institute of Coimbra. Currently this project is over, but the platform is maintained by the same team. Sightings are reported by users who register at the platform and submit them, either directly on the website (https://invasoras.pt/pt/mapeamento) or using an app for Android (https://play.google.com/store/apps/details?id=pt.uc.invasoras2) and iOS (https://apps.apple.com/pt/app/plantas-invasoras-em-portugal/id1501776731) devices. Only validated sightings are available on the dataset. Validation is made based on photographs submitted along with the sightings by experts from the platform INVASORAS.PT team. As with all citizen science projects there is some risk of erroneous records and duplication of sightings.

  11. s

    SpaceFinder App locations DLR - Dataset - data.smartdublin.ie

    • data.smartdublin.ie
    Updated Aug 15, 2023
    + more versions
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    (2023). SpaceFinder App locations DLR - Dataset - data.smartdublin.ie [Dataset]. https://data.smartdublin.ie/dataset/spacefinder-app-locations-dlr
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    Dataset updated
    Aug 15, 2023
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset provides the locations of the 36 accessible parking spaces included in the dlr SpaceFinder App. The app provides real-time information on the location & live availability of the 36 accessible parking spaces in Dún Laoghaire Town. Through the app, sensors at each of these locations will notify blue badge users whether the space is free or occupied and allow users can accurately pinpoint and navigate to available accessible parking spaces. Within this dataset, you'll find information on 36 distinct accessible parking locations in Dún Laoghaire Town. Each entry is defined by its unique ID and includes geographical data: latitude and longitude coordinates and ITM coordinates. The app is available on Apple and Android app stores.

  12. Penetration rate of smartphones worldwide 2014-2029

    • statista.com
    Updated Jul 18, 2025
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    Statista Research Department (2025). Penetration rate of smartphones worldwide 2014-2029 [Dataset]. https://www.statista.com/topics/840/smartphones/
    Explore at:
    Dataset updated
    Jul 18, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    The global smartphone penetration in was forecast to continuously increase between 2024 and 2029 by in total 20.3 percentage points. After the fifteenth consecutive increasing year, the penetration is estimated to reach 74.98 percent and therefore a new peak in 2029. Notably, the smartphone penetration of was continuously increasing over the past years.The penetration rate refers to the share of the total population.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the smartphone penetration in countries like North America and the Americas.

  13. Number of smartphone users in the Philippines 2014-2029

    • statista.com
    + more versions
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    Statista Research Department, Number of smartphone users in the Philippines 2014-2029 [Dataset]. https://www.statista.com/topics/8230/smartphones-market-in-the-philippines/
    Explore at:
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    Philippines
    Description

    The number of smartphone users in the Philippines was forecast to increase between 2024 and 2029 by in total 5.6 million users (+7.29 percent). This overall increase does not happen continuously, notably not in 2026, 2027, 2028 and 2029. The smartphone user base is estimated to amount to 82.33 million users in 2029. Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of smartphone users in countries like Thailand and Indonesia.

  14. Penetration rate of smartphones in the Philippines 2014-2029

    • statista.com
    + more versions
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    Statista Research Department, Penetration rate of smartphones in the Philippines 2014-2029 [Dataset]. https://www.statista.com/topics/8230/smartphones-market-in-the-philippines/
    Explore at:
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    Philippines
    Description

    The smartphone penetration in the Philippines was forecast to continuously decrease between 2024 and 2029 by in total 6.4 percentage points. According to this forecast, in 2029, the penetration will have decreased for the fourth consecutive year to 65.75 percent. The penetration rate refers to the share of the total population.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the smartphone penetration in countries like Laos and Malaysia.

  15. Number of mobile broadband connections in the Philippines 2014-2029

    • statista.com
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    Statista Research Department, Number of mobile broadband connections in the Philippines 2014-2029 [Dataset]. https://www.statista.com/topics/8230/smartphones-market-in-the-philippines/
    Explore at:
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    Philippines
    Description

    The number of mobile broadband connections in the Philippines was forecast to continuously increase between 2024 and 2029 by in total 18.3 million connections (+20.46 percent). After the ninth consecutive increasing year, the number of connections is estimated to reach 107.69 million connections and therefore a new peak in 2029. Mobile broadband connections include cellular connections with a download speed of at least 256 kbit/s (without satellite or fixed-wireless connections). Cellular Internet-of-Things (IoT) or machine-to-machine (M2M) connections are excluded. The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of mobile broadband connections in countries like Vietnam and Laos.

  16. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Statista (2025). Market share of mobile operating systems worldwide 2009-2025, by quarter [Dataset]. https://www.statista.com/statistics/272698/global-market-share-held-by-mobile-operating-systems-since-2009/
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Market share of mobile operating systems worldwide 2009-2025, by quarter

Explore at:
392 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 23, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Worldwide
Description

Android maintained its position as the leading mobile operating system worldwide in the first quarter of 2025 with a market share of about ***** percent. Android's closest rival, Apple's iOS, had a market share of approximately ***** percent during the same period. The leading mobile operating systems Both unveiled in 2007, Google’s Android and Apple’s iOS have evolved through incremental updates introducing new features and capabilities. The latest version of iOS, iOS 18, was released in September 2024, while the most recent Android iteration, Android 15, was made available in September 2023. A key difference between the two systems concerns hardware - iOS is only available on Apple devices, whereas Android ships with devices from a range of manufacturers such as Samsung, Google and OnePlus. In addition, Apple has had far greater success in bringing its users up to date. As of February 2024, ** percent of iOS users had iOS 17 installed, while in the same month only ** percent of Android users ran the latest version. The rise of the smartphone From around 2010, the touchscreen smartphone revolution had a major impact on sales of basic feature phones, as the sales of smartphones increased from *** million units in 2008 to **** billion units in 2023. In 2020, smartphone sales decreased to **** billion units due to the coronavirus (COVID-19) pandemic. Apple, Samsung, and lately also Xiaomi, were the big winners in this shift towards smartphones, with BlackBerry and Nokia among those unable to capitalize.

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