In 2024, the United States was the leading app market, with the Apple App Store and the Google App Store generating approximately 31 billion U.S. dollars of in-app revenues. China was the second-largest app market, as in-app revenues in the region generated approximately 17.34 billion U.S. dollars. Japan ranked third, as the region generated around 11.25 billion U.S. dollars in app revenues for the examined period.

As of May 2024, 44 percent of the total revenues generated by the global app market came from subscriptions. Other monetization methods such as paid downloads and in-app purchases represented the most popular types of revenue streams for global app publishers. Overall, 56 percent of total app revenues came from other monetization methods.

The global big data market is forecasted to grow to 103 billion U.S. dollars by 2027, more than double its expected market size in 2018. With a share of 45 percent, the software segment would become the large big data market segment by 2027.

What is Big data?

Big data is a term that refers to the kind of data sets that are too large or too complex for traditional data processing applications. It is defined as having one or some of the following characteristics: high volume, high velocity or high variety. Fast-growing mobile data traffic, cloud computing traffic, as well as the rapid development of technologies such as artificial intelligence (AI) and the Internet of Things (IoT) all contribute to the increasing volume and complexity of data sets.

Big data analytics

Advanced analytics tools, such as predictive analytics and data mining, help to extract value from the data and generate new business insights. The global big data and business analytics market was valued at 169 billion U.S. dollars in 2018 and is expected to grow to 274 billion U.S. dollars in 2022. As of November 2018, 45 percent of professionals in the market research industry reportedly used big data analytics as a research method.

The global graph database market size reached USD 2.0 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 8.6 Billion by 2033, exhibiting a growth rate (CAGR) of 17.57% during 2025-2033. The increasing adoption of graph databases in cybersecurity for threat detection and network analysis, growing demand for real-time analytics and AI-driven insights, and expanding application in industries, such as healthcare and finance, for data integration and personalized services, are some of the key factors catalyzing the market growth.

Report Attribute	Key Statistics
Base Year	2024
Forecast Years	2025-2033
Historical Years	2019-2024
Market Size in 2024	USD 2.0 Billion
Market Forecast in 2033	USD 8.6 Billion
Market Growth Rate ​​​​​​​2025-2033	17.57%

IMARC Group provides an analysis of the key trends in each segment of the global graph database market report, along with forecasts at the global, regional, and country levels from 2025-2033. Our report has categorized the market based on component, type of database, analysis type, deployment model, application, and industry vertical.

Graph Database Market size was valued at USD 2.86 Billion in 2024 and is projected to reach USD 14.58 Billion by 2032, growing at a CAGR of 22.6% from 2026 to 2032. Global Graph Database Market DriversThe growth and development of the Graph Database Market is attributed to certain main market drivers. These factors have a big impact on how Graph Database are demanded and adopted in different sectors. Several of the major market forces are as follows:Growth of Connected Data: Graph databases are excellent at expressing and querying relationships as businesses work with datasets that are more complex and interconnected. Graph databases are becoming more and more in demand as connected data gains significance across multiple industries.Knowledge Graph Emergence: In fields like artificial intelligence, machine learning, and data analytics, knowledge graphs—which arrange information in a graph structure—are becoming more and more popular. Knowledge graphs can only be created and queried via graph databases, which is what is causing their widespread use.Analytics and Machine Learning Advancements: Graph databases handle relationships and patterns in data effectively, enabling applications related to advanced analytics and machine learning. Graph databases are becoming more and more in demand when combined with analytics and machine learning as businesses want to extract more insights from their data.Real-Time Data Processing: Graph databases can process data in real-time, which makes them appropriate for applications that need quick answers and insights. In situations like fraud detection, recommendation systems, and network analysis, this is especially helpful.Increasing Need for Security and Fraud Detection: Graph databases are useful for fraud security and detection applications because they can identify patterns and abnormalities in linked data. The growing need for graph databases in security solutions is a result of the ongoing evolution of cybersecurity threats.

Context

Mobile apps are everywhere. They are easy to create and can be lucrative. Because of these two factors, more and more apps are being developed. In this notebook, we will do a comprehensive analysis of the Android app market by comparing over ten thousand apps in Google Play across different categories. We'll look for insights in the data to devise strategies to drive growth and retention.

The global database management system (DBMS) market revenue grew to ** billion U.S. dollars in 2020. Cloud DBMS accounted for the majority of the overall market growth, as database systems are migrating to cloud platforms. Database market The database market consists of paid database software such as Oracle and Microsoft SQL Server, as well as free, open-source software options like PostgreSQL and MongolDB. Database Management Systems (DBMSs) provide a platform through which developers can organize, update, and control large databases, with products like Oracle, MySQL, and Microsoft SQL Server being the most widely used in the market. Database management software Knowledge of the programming languages related to these databases is becoming an increasingly important asset for software developers around the world, and database management skills such as MongoDB and Elasticsearch are seen as highly desirable. In addition to providing developers with the tools needed to operate databases, DBMS are also integral to the way that consumers access information through applications, which further illustrates the importance of the software.

Apple App Store Key StatisticsApps & Games in the Apple App StoreApps in the Apple App StoreGames in the Apple App StoreMost Popular Apple App Store CategoriesPaid vs Free Apps in Apple App...

Open-Source Database Software Market size was valued at USD 10.00 Billion in 2024 and is projected to reach USD 35.83 Billion by 2032, growing at a CAGR of 20% during the forecast period 2026-2032.

Global Open-Source Database Software Market Drivers

The market drivers for the Open-Source Database Software Market can be influenced by various factors. These may include:

Cost-Effectiveness: Compared to proprietary systems, open-source databases frequently have lower initial expenses, which attracts organizations—especially startups and small to medium-sized enterprises (SMEs) with tight budgets. Flexibility and Customisation: Open-source databases provide more possibilities for customization and flexibility, enabling businesses to modify the database to suit their unique needs and grow as necessary. Collaboration and Community Support: Active developer communities that share best practices, support, and contribute to the continued development of open-source databases are beneficial. This cooperative setting can promote quicker problem solving and innovation. Performance and Scalability: A lot of open-source databases are made to scale horizontally across several nodes, which helps businesses manage expanding data volumes and keep up performance levels as their requirements change. Data Security and Sovereignty: Open-source databases provide businesses more control over their data and allow them to decide where to store and use it, which helps to allay worries about compliance and data sovereignty. Furthermore, open-source code openness can improve security by making it simpler to find and fix problems. Compatibility with Contemporary Technologies: Open-source databases are well-suited for contemporary application development and deployment techniques like microservices, containers, and cloud-native architectures since they frequently support a broad range of programming languages, frameworks, and platforms. Growing Cloud Computing Adoption: Open-source databases offer a flexible and affordable solution for managing data in cloud environments, whether through self-managed deployments or via managed database services provided by cloud providers. This is because more and more organizations are moving their workloads to the cloud. Escalating Need for Real-Time Insights and Analytics: Organizations are increasingly adopting open-source databases with integrated analytics capabilities, like NoSQL and NewSQL databases, as a means of instantly obtaining actionable insights from their data.

[ADVISORY] IMPORTANT

Instructions for citation:

If you use this dataset anywhere in your work, kindly cite as the below: L. Gupta, "Google Play Store Apps," Feb 2019. [Online]. Available: https://www.kaggle.com/lava18/google-play-store-apps

Context

While many public datasets (on Kaggle and the like) provide Apple App Store data, there are not many counterpart datasets available for Google Play Store apps anywhere on the web. On digging deeper, I found out that iTunes App Store page deploys a nicely indexed appendix-like structure to allow for simple and easy web scraping. On the other hand, Google Play Store uses sophisticated modern-day techniques (like dynamic page load) using JQuery making scraping more challenging.

Content

Each app (row) has values for catergory, rating, size, and more.

Acknowledgements

This information is scraped from the Google Play Store. This app information would not be available without it.

Inspiration

The Play Store apps data has enormous potential to drive app-making businesses to success. Actionable insights can be drawn for developers to work on and capture the Android market!

BASE YEAR	2024
HISTORICAL DATA	2019 - 2023
REGIONS COVERED	North America, Europe, APAC, South America, MEA
REPORT COVERAGE	Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
MARKET SIZE 2024	9.35(USD Billion)
MARKET SIZE 2025	10.4(USD Billion)
MARKET SIZE 2035	30.0(USD Billion)
SEGMENTS COVERED	Application, Deployment Model, Type, End Use, Regional
COUNTRIES COVERED	US, Canada, Germany, UK, France, Russia, Italy, Spain, Rest of Europe, China, India, Japan, South Korea, Malaysia, Thailand, Indonesia, Rest of APAC, Brazil, Mexico, Argentina, Rest of South America, GCC, South Africa, Rest of MEA
KEY MARKET DYNAMICS	increasing data volume, demand for low latency, rise of cloud computing, growing e-commerce activities, need for real-time analytics
MARKET FORECAST UNITS	USD Billion
KEY COMPANIES PROFILED	Datastax, Apache Software Foundation, Amazon Web Services, Memcached, Microsoft, GigaSpaces, Google, Redis Labs, Oracle, Alibaba Cloud, SAP, Couchbase, Aerospike, TIBCO Software, Hazelcast, Salesforce, IBM
MARKET FORECAST PERIOD	2025 - 2035
KEY MARKET OPPORTUNITIES	Real-time data processing needs, Increased cloud adoption rates, Growth in IoT applications, Demand for faster applications, Rising importance of data analytics
COMPOUND ANNUAL GROWTH RATE (CAGR)	11.2% (2025 - 2035)

During the first quarter of 2024, YouTube shorts recorded the highest engagement rate across all short video platforms and in-app features analyzed. Content hosted on YouTube in form of shorts had an engagement rate of 5.91 percent, while TikTok reported an engagement rate of approximately 5.75 percent. Facebook Reels had an engagement rate of around two percent, making the platform rank last for short-format user engagement.

Global Data Management System DBMS market size 2025 was XX Million. Data Management System DBMS Industry compound annual growth rate (CAGR) will be XX% from 2025 till 2033.

Use the OpenWeb Ninja Google Play App Store Data API to access comprehensive data on Google Play Store, including Android Apps / Games, reviews, top charts, search, and more. Our extensive dataset provides over 40 app store data points, enabling you to gain deep insights into the market.

The App Store Data dataset includes all key app details:

App Name, Description, Rating, Photos, Downloads, Version Information, App Size, Permissions, Developer and Contact Information, Consumer Review Data.

Agentic AI Applications in Vector Database Market Report is Segmented by Deployment Mode (Cloud-Managed, Self-Hosted, & Hybrid), Vector Database Type (Purpose-Built Vector Databases, & More), Application (Conversational AI and RAG, Autonomous Agents and Workflow Orchestration, & More), End-User Industry (IT and Telecom, BFSI, and More), and Geography (North America, South America, Europe, Asia-Pacific, and Middle East and Africa).

By 2025, the managed database services market will likely hit USD 445,020.1 million and grow to USD 1,497,335 million by 2035, with a CAGR of 12.9%. The rise of using multi-cloud and mixed cloud plans, rising AI use for smart database upkeep, and more people using Database-as-a-Service are guiding the future of the industry. Also, more worry about keeping data safe and following rules is driving market growth.

Metric	Value
Market Size (2025E)	USD 445,020.1 Million
Market Value (2035F)	USD 1,497,335 Million
CAGR (2025 to 2035)	12.9%

Country-wise Insights

Country	CAGR (2025 to 2035)
USA	13.1%

Country	CAGR (2025 to 2035)
UK	12.7%

Region	CAGR (2025 to 2035)
European Union (EU)	12.9%

Country	CAGR (2025 to 2035)
Japan	13.0%

Country	CAGR (2025 to 2035)
South Korea	13.2%

Managed Database Services Market - Segmentation Outlook

Service	Market Share (2025)
Database Administration	38.0%

Application	Market Share (2025)
Customer Relationship Management (CRM)	46.0%

Competitive Outlook

Company Name	Estimated Market Share (%)
Amazon Web Services (AWS)	18-22%
Microsoft Corporation (Azure)	14-18%
Google Cloud Platform (GCP)	12-16%
Oracle Corporation	10-14%
IBM Corporation	6-10%
Other Companies (combined)	30-40%

According to Cognitive Market Research, the global Ai Training Data market size is USD 1865.2 million in 2023 and will expand at a compound annual growth rate (CAGR) of 23.50% from 2023 to 2030.

The demand for Ai Training Data is rising due to the rising demand for labelled data and diversification of AI applications.
Demand for Image/Video remains higher in the Ai Training Data market.
The Healthcare category held the highest Ai Training Data market revenue share in 2023.
North American Ai Training Data will continue to lead, whereas the Asia-Pacific Ai Training Data market will experience the most substantial growth until 2030.

Market Dynamics of AI Training Data Market

Key Drivers of AI Training Data Market

Rising Demand for Industry-Specific Datasets to Provide Viable Market Output

A key driver in the AI Training Data market is the escalating demand for industry-specific datasets. As businesses across sectors increasingly adopt AI applications, the need for highly specialized and domain-specific training data becomes critical. Industries such as healthcare, finance, and automotive require datasets that reflect the nuances and complexities unique to their domains. This demand fuels the growth of providers offering curated datasets tailored to specific industries, ensuring that AI models are trained with relevant and representative data, leading to enhanced performance and accuracy in diverse applications.

In July 2021, Amazon and Hugging Face, a provider of open-source natural language processing (NLP) technologies, have collaborated. The objective of this partnership was to accelerate the deployment of sophisticated NLP capabilities while making it easier for businesses to use cutting-edge machine-learning models. Following this partnership, Hugging Face will suggest Amazon Web Services as a cloud service provider for its clients.

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Advancements in Data Labelling Technologies to Propel Market Growth

The continuous advancements in data labelling technologies serve as another significant driver for the AI Training Data market. Efficient and accurate labelling is essential for training robust AI models. Innovations in automated and semi-automated labelling tools, leveraging techniques like computer vision and natural language processing, streamline the data annotation process. These technologies not only improve the speed and scalability of dataset preparation but also contribute to the overall quality and consistency of labelled data. The adoption of advanced labelling solutions addresses industry challenges related to data annotation, driving the market forward amidst the increasing demand for high-quality training data.

In June 2021, Scale AI and MIT Media Lab, a Massachusetts Institute of Technology research centre, began working together. To help doctors treat patients more effectively, this cooperation attempted to utilize ML in healthcare.

www.ncbi.nlm.nih.gov/pmc/articles/PMC7325854/

Restraint Factors Of AI Training Data Market

Data Privacy and Security Concerns to Restrict Market Growth

A significant restraint in the AI Training Data market is the growing concern over data privacy and security. As the demand for diverse and expansive datasets rises, so does the need for sensitive information. However, the collection and utilization of personal or proprietary data raise ethical and privacy issues. Companies and data providers face challenges in ensuring compliance with regulations and safeguarding against unauthorized access or misuse of sensitive information. Addressing these concerns becomes imperative to gain user trust and navigate the evolving landscape of data protection laws, which, in turn, poses a restraint on the smooth progression of the AI Training Data market.

How did COVID–19 impact the Ai Training Data market?

The COVID-19 pandemic has had a multifaceted impact on the AI Training Data market. While the demand for AI solutions has accelerated across industries, the availability and collection of training data faced challenges. The pandemic disrupted traditional data collection methods, leading to a slowdown in the generation of labeled datasets due to restrictions on physical operations. Simultaneously, the surge in remote work and the increased reliance on AI-driven technologies for various applications fueled the need for diverse and relevant training data. This duali...

Find detailed analysis in Market Research Intellect's Relational Database Software Market Report, estimated at USD 51.2 billion in 2024 and forecasted to climb to USD 76.4 billion by 2033, reflecting a CAGR of 5.7%.Stay informed about adoption trends, evolving technologies, and key market participants.

BASE YEAR	2024
HISTORICAL DATA	2019 - 2023
REGIONS COVERED	North America, Europe, APAC, South America, MEA
REPORT COVERAGE	Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
MARKET SIZE 2024	3.75(USD Billion)
MARKET SIZE 2025	4.25(USD Billion)
MARKET SIZE 2035	15.0(USD Billion)
SEGMENTS COVERED	Application, Deployment Model, Data Model, End Use, Regional
COUNTRIES COVERED	US, Canada, Germany, UK, France, Russia, Italy, Spain, Rest of Europe, China, India, Japan, South Korea, Malaysia, Thailand, Indonesia, Rest of APAC, Brazil, Mexico, Argentina, Rest of South America, GCC, South Africa, Rest of MEA
KEY MARKET DYNAMICS	Growing demand for real-time analytics, Increasing adoption of cloud services, Rising need for data synchronization, Expanding usage of IoT applications, High scalability and performance requirements
MARKET FORECAST UNITS	USD Billion
KEY COMPANIES PROFILED	Neo4j, MemSQL, Cloudera, Microsoft, MongoDB, Google, Cassandra, Oracle, Couchbase, Amazon, Firebase, Aerospike, Timescale, Redis, Snowflake, IBM
MARKET FORECAST PERIOD	2025 - 2035
KEY MARKET OPPORTUNITIES	Cloud-based data solutions, Increasing demand for IoT applications, Real-time analytics for business intelligence, Enhanced data security features, Growth in mobile application development
COMPOUND ANNUAL GROWTH RATE (CAGR)	13.4% (2025 - 2035)

Genomic Data Set for Real World Evidence (RWE) Applications Market is projected to grow USD 1,704.60 Million in 2032 and grow at a CAGR of 15.2% according to market forecast.