E-commerce platform search volume indicating direct purchase consideration

Discover the booming Cloud Data Platform market! This in-depth analysis reveals a $50 billion market in 2025, projected to reach $150 billion by 2033, driven by cloud adoption, big data analytics, and AI. Explore key trends, restraints, and regional market shares. Learn about leading companies and application segments shaping this dynamic landscape.

A multidisciplinary repository of public data sets such as the Human Genome and US Census data that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge for the community. Anyone can access these data sets from their Amazon Elastic Compute Cloud (Amazon EC2) instances and start computing on the data within minutes. Users can also leverage the entire AWS ecosystem and easily collaborate with other AWS users. If you have a public domain or non-proprietary data set that you think is useful and interesting to the AWS community, please submit a request and the AWS team will review your submission and get back to you. Typically the data sets in the repository are between 1 GB to 1 TB in size (based on the Amazon EBS volume limit), but they can work with you to host larger data sets as well. You must have the right to make the data freely available.

In the second quarter of 2025, net sales of Amazon Web Services (AWS) reached ** percent, having remained on the same level as in the previous quarter. AWS is one of Amazon’s strongest revenue segments, generating over *** billion U.S. dollars in 2024 net sales, up from *** billion U.S. dollars in 2023. On October 20, 2025, the provider experienced a 15-hour outage, which disrupted operations in various industries ranging from social media through banks to smart home devices. Some of the affected companies include Snapchat, Reddit, Lloyds Bank, Roblox, and Zoom. Amazon Web Services Amazon Web Services (AWS) provides on-demand cloud platforms and APIs through a pay-as-you-go model to customers. AWS launched in 2002, providing general services and tools, and produced its first cloud products in 2006. Today, more than *** different cloud services for a variety of technologies and industries have already been released. AWS ranks as one of the most popular public cloud infrastructure and platform services running applications worldwide in 2020, ahead of Microsoft Azure and Google cloud services. Cloud computing Cloud computing is essentially the delivery of online computing services to customers. As enterprises continually migrate their applications and data to the cloud instead of storing them on local machines, it becomes possible to access resources from different locations. Some of the key services of the AWS ecosystem for cloud applications include storage, databases, security tools, and management tools. AWS is among the most popular cloud providers Some of the largest globally operating enterprises use AWS for their cloud services, including Netflix, BBC, and Baidu. Accordingly, AWS is one of the leading cloud providers in the global cloud market. Due to its continuously expanding portfolio of services and deepening of expertise, the company continues to be not only an important cloud service provider but also a business partner.

AWS Managed Services Market size is estimated at USD 10.84 Billion in 2024 and is projected to reach USD 27.89 Billion by 2032, growing at a CAGR of 12.54% from 2026 to 2032.

AWS Managed Services Market: Definition/Overview

AWS Managed Services are offered by Amazon Web Services and are designed to be overseen by AWS on the customer's behalf. These services encompass a wide range of tasks associated with cloud computing, including infrastructure management, security maintenance, platform configuration, and application optimization.

Through AWS Managed Services, organizations can benefit from proactive monitoring, automated patching, backup management, and security compliance, among other features. It provides access to AWS-certified experts who handle tasks such as provisioning, configuring, and scaling resources based on organizational needs. By leveraging AWS Managed Services, organizations can streamline their operations, reduce operational overhead, and focus on their core business objectives while AWS takes care of the underlying infrastructure and management tasks.

In 2024, Amazon Web Services (AWS) generated ****** billion US dollars with its cloud services. From 2013 until today, the annual revenue of AWS cloud computing and hosting solutions continually increased.

Amazon—additional information Amazon.com went online in 1995, initially as a book store, and achieved almost immediate success. In 1998, the store expanded to include a music and video store and different other products, such as apparel and consumer electronics, in the following years. The company is the undisputed leader of the e-retail market in the United States, ranking ahead of walmart.com and apple.com in terms of revenue. Amazon Web Services In 2006, AWS launched as a cloud computing platform to provide online services. Amazon Elastic Compute Cloud and Amazon S3, which provide large virtual computing capacity, are the most well-known of these services. The company has dozens of locations in ** different regions across the world and is continually expanding its global infrastructure to ensure low latency through proximity to the user. From these data centers, Amazon is offering more than *** fully featured services to its global customer base. Video streaming service Netflix is one of AWS’s largest customers, using Amazon’s services to store their content on servers throughout the world. Among its more than *********** active users, AWS also lists other well-known organizations from various industries, such as Disney, the UK Ministry of Justice, Kellogg’s, Guardian News and Media, and the European Space Agency.

The Cloud Data Platform (CDP) market is experiencing robust growth, driven by the increasing need for organizations to manage and analyze ever-expanding data volumes from diverse sources. The market, estimated at $50 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 25% from 2025 to 2033, reaching an estimated $250 billion by 2033. This significant expansion is fueled by several key factors. The rising adoption of cloud computing, coupled with the demand for real-time data analytics and improved data governance, is creating a fertile ground for CDP solutions. Furthermore, the increasing complexity of data landscapes, including the proliferation of data lakes and data warehouses, necessitates sophisticated platforms capable of unifying and streamlining data management processes across various applications. Industries like banking, telecommunications, and life sciences, with their massive data volumes and regulatory requirements, are at the forefront of CDP adoption, further boosting market growth. However, challenges such as data security concerns, integration complexities, and the need for skilled professionals to manage these complex systems could potentially restrain market expansion to some extent. The segmentation of the CDP market reveals diverse application areas and platform types. Data warehouse and data integration solutions currently dominate the market, but data lakes are rapidly gaining traction due to their scalability and cost-effectiveness. Within application segments, the banking, telecommunications, and government sectors are exhibiting the highest adoption rates, driven by the need for enhanced customer insights and operational efficiency. Major players in this space, including Amazon Web Services, Google, Microsoft, and Snowflake, are continuously innovating and expanding their offerings, fostering competition and driving further market growth. The increasing adoption of hybrid and multi-cloud strategies further fuels the need for comprehensive CDP solutions that can effectively manage data across disparate environments. The geographical distribution of the market showcases strong growth in North America and Europe, while Asia-Pacific is emerging as a significant region with high potential for future expansion.

The Autonomous Data Platform market is booming, projected to reach $1.77B by 2025 with a 20.33% CAGR. Learn about key drivers, trends, and leading companies shaping this dynamic sector, including cloud adoption, data governance needs, and competitive landscape analysis. Explore market segmentation by organization size, deployment type, and vertical. Key drivers for this market are: , Growing Adoption of Cognitive Computing Technology and Advanced Analytics; Expanding Volume of Unstructured Data Due to the Phenomenal Growth of Interconnected Devices and Social Media. Potential restraints include: , Complex Analytical Process Requiring Skilled Professionals Services. Notable trends are: Retail Vertical is Expected to Register a Significant Growth.

Discover the booming Data Middle Platform Solutions market! This comprehensive analysis reveals a $50B market in 2025, growing at 15% CAGR. Explore key drivers, trends, restraints, and leading players like Microsoft Azure, AWS, and Google Cloud. Get insights into regional market share and future projections until 2033.

The Data Marketplace Platform market is booming, projected to reach $5 billion by 2025, driven by increased demand for data-driven insights and cloud adoption. Discover key trends, leading companies (AWS, Microsoft, Snowflake), and growth projections in this comprehensive market analysis.

In the fourth quarter of 2024, the most popular vendor in the cloud infrastructure services market, Amazon Web Services (AWS), controlled ** percent of the entire market. Microsoft Azure takes second place with ** percent market share, followed by Google Cloud with ** percent market share. Together, these three cloud vendors account for ** percent of total spend in the fourth quarter of 2024. Organizations use cloud services from these vendors for machine learning, data analytics, cloud native development, application migration, and other services. AWS Services Amazon Web Services is used by many organizations because it offers a wide variety of services and products to its customers that improve business agility while being secure and reliable. One of AWS’s most used services is Amazon EC2, which lets customers create virtual machines for their strategic projects while spending less time on maintaining servers. Another important service is Amazon Simple Storage Service (S3), which offers a secure file storage service. In addition, Amazon also offers security, website infrastructure management, and identity and access management solutions. Cloud infrastructure services Vendors offering cloud services to a global customer base do so through different types of cloud computing, which include infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Further, there are different cloud computing deployment models available for customers, namely private cloud and public cloud, as well as community cloud and hybrid cloud. A cloud deployment model is defined based on the location where the deployment resides, and who has access to and control over the infrastructure.

The Data Middle Platform Solutions market is experiencing robust growth, driven by the increasing need for efficient data management and advanced analytics across diverse sectors. The market's expansion is fueled by the rising adoption of cloud-based solutions, the proliferation of big data, and the escalating demand for real-time insights to support faster decision-making. Key applications include finance (for risk management and fraud detection), retail (for personalized customer experiences and supply chain optimization), government (for improved citizen services and data-driven policymaking), and industrial sectors (for predictive maintenance and operational efficiency). The market is segmented by platform type, with Data Integration Platforms, Data Warehousing Platforms, Big Data Platforms, and Analytics Platforms experiencing significant demand. While North America currently holds a dominant market share due to early adoption and technological advancements, Asia-Pacific is projected to witness the fastest growth rate in the coming years, driven by burgeoning digital economies and increasing government investments in digital infrastructure. Competitive pressures are high, with established players like Microsoft Azure, Amazon Web Services, and Google Cloud Platform competing with specialized vendors and emerging innovative companies. The market faces challenges such as data security concerns, the complexity of data integration, and the need for skilled professionals to manage these sophisticated platforms. However, ongoing technological innovation and the growing realization of the strategic importance of data are expected to overcome these challenges, leading to sustained market growth. The forecast period (2025-2033) promises further expansion, propelled by the continued digital transformation across industries. Specific growth drivers include the Internet of Things (IoT) generating vast amounts of data, the increasing adoption of artificial intelligence (AI) and machine learning (ML) for data analysis, and the growing emphasis on data governance and compliance. While challenges persist in areas such as data privacy and regulatory compliance, the long-term outlook for Data Middle Platform Solutions remains highly positive, driven by the ongoing strategic importance of data across all sectors of the global economy. We project a sustained Compound Annual Growth Rate (CAGR) reflecting this positive trajectory and the increasing market penetration across diverse geographic regions. Further segmentation analysis would reveal granular insights into specific platform adoption rates and regional growth patterns.

Context: The "Amazon Books Dataset" is a meticulously curated collection of data related to books available on the Amazon platform, with a primary focus on computer science literature. This dataset holds significant importance for researchers, industry experts, and enthusiasts who are interested in gaining profound insights into the world of computer science literature, publishing trends, and the broader book market. Computer science is at the forefront of technological innovation and is a driving force in shaping the modern world. Understanding the dynamics of the Amazon book market, particularly in the realm of computer science, is essential for various stakeholders in the publishing, technology, and retail industries.

Data Source: The data for this dataset has been meticulously sourced and compiled from Amazon's extensive catalog of books, with a specific emphasis on books related to computer science. The information is current as of the dataset's creation date and may continue to evolve as new books are published and existing ones undergo changes in attributes such as ratings and prices.

Content: The "Amazon Books Catalog Dataset" provides a rich and comprehensive array of data points for each book listed on Amazon, with a primary focus on computer science literature. These data points empower users to conduct in-depth analyses and uncover valuable insights. Here are the key columns included in this dataset:

1. Title: The title of the book, represents its core identity.
2. Description: A concise yet informative overview of the book's content and themes.
3. Author: The name(s) of the author(s) responsible for creating the literary work.
4. ISBN-10: The International Standard Book Number in the 10-digit format, aiding in precise identification.
5. ISBN-13: The International Standard Book Number in the 13-digit format, enhancing global recognition.
6. Publish Date: The date on which the book was officially published, marking its entry into the literary world.
7. Edition: Information about the edition of the book, if applicable, providing insights into its various releases.
8. Best Seller: A binary indicator (1 or 0) signifying whether the book has achieved best-seller status.
9. Top Rated: A binary indicator (1 or 0) highlighting whether the book has received high ratings and acclaim from readers.
10. Rating: The average rating awarded to the book by Amazon customers, offering an assessment of its quality.
11. Review Count: The total number of user reviews posted for the book, reflecting reader engagement and feedback.
12. Price: The current price of the book on the Amazon platform, influences purchase decisions.

Potential Use Cases: This dataset, with its focus on computer science literature, presents a unique opportunity for research and analysis in fields such as:

• Technology Trends: Analyzing emerging trends in computer science literature, including topics, technologies, and subfields.
• Educational Insights: Investigating the popularity of computer science textbooks and learning materials.
• Author Impact: Assessing the influence and contributions of authors within the computer science domain.
• Market Analysis: Understanding pricing dynamics and factors influencing the success of computer science books.

Researchers, analysts, and computer science enthusiasts can leverage this dataset to explore the intricate world of computer science literature, uncover market trends, and contribute to a deeper understanding of the evolving landscape of technology and knowledge dissemination on one of the world's largest online marketplaces.

The Big Data Platform market is booming, projected to reach $120.3 Billion by 2033 with a 9.1% CAGR. This comprehensive analysis explores market drivers, trends, restraints, and key players like Microsoft, Google, and AWS, offering insights into regional market share and future growth potential. Discover the latest on cloud-based vs. on-premise solutions and their applications across key sectors.

Discover the explosive growth of the Big Data Platform market, projected to reach $57.9B in 2025 with a 9.1% CAGR. This in-depth analysis explores key drivers, trends, and challenges, featuring insights from leading players like Microsoft, Google, and AWS. Learn about market segmentation, regional growth, and future projections for this dynamic sector.

Network was collected by crawling Amazon website. It is based on Customers Who Bought This Item Also Bought feature of the Amazon website. If a product i is frequently co-purchased with product j, the graph contains a directed edge from i to j.

The data was collected by crawling Amazon website and contains product metadata and review information about 548,552 different products (Books, music CDs, DVDs and VHS video tapes).

For each product the following information is available:

Title Salesrank List of similar products (that get co-purchased with the current product) Detailed product categorization Product reviews: time, customer, rating, number of votes, number of people that found the review helpful

Stanford Network Analysis Platform (SNAP) is a general purpose, high performance system for analysis and manipulation of large networks. Graphs consists of nodes and directed/undirected/multiple edges between the graph nodes. Networks are graphs with data on nodes and/or edges of the network.

The core SNAP library is written in C++ and optimized for maximum performance and compact graph representation. It easily scales to massive networks with hundreds of millions of nodes, and billions of edges. It efficiently manipulates large graphs, calculates structural properties, generates regular and random graphs, and supports attributes on nodes and edges. Besides scalability to large graphs, an additional strength of SNAP is that nodes, edges and attributes in a graph or a network can be changed dynamically during the computation.

SNAP was originally developed by Jure Leskovec in the course of his PhD studies. The first release was made available in Nov, 2009. SNAP uses a general purpose STL (Standard Template Library)-like library GLib developed at Jozef Stefan Institute. SNAP and GLib are being actively developed and used in numerous academic and industrial projects.

http://snap.stanford.edu/data/index.html#amazon

The Data Science Platform market is experiencing robust growth, projected to reach $10.15 billion in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 23.50% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing volume and complexity of data generated across diverse industries necessitates sophisticated platforms for analysis and insights extraction. Businesses are increasingly adopting cloud-based solutions for their scalability, cost-effectiveness, and accessibility, driving the growth of the cloud deployment segment. Furthermore, the rising demand for advanced analytics capabilities across sectors like BFSI (Banking, Financial Services, and Insurance), retail and e-commerce, and IT & Telecom is significantly boosting market demand. The availability of robust and user-friendly platforms is empowering businesses of all sizes, from SMEs to large enterprises, to leverage data science effectively for improved decision-making and competitive advantage. The market is witnessing the emergence of innovative solutions such as automated machine learning (AutoML) and integrated platforms that combine data preparation, model building, and deployment capabilities. The market segmentation reveals significant opportunities across various offerings and deployment models. While the platform segment holds a larger share, the services segment is poised for significant growth driven by the need for expert consulting and support in data science projects. Geographically, North America currently dominates the market, but the Asia-Pacific region is expected to witness faster growth due to increasing digitalization and technological advancements. Key players like IBM, Google, Microsoft, and Amazon are driving innovation and competition, with new entrants continuously emerging, adding to the market's dynamism. While challenges such as data security and privacy concerns remain, the overall market outlook is exceptionally positive, promising considerable growth over the forecast period. Continued technological innovation, coupled with rising adoption across a wider array of industries, will be central to the market's continued expansion. Recent developments include: November 2023 - Stagwell announced a partnership with Google Cloud and SADA, a Google Cloud premier partner, to develop generative AI (gen AI) marketing solutions that support Stagwell agencies, client partners, and product development within the Stagwell Marketing Cloud (SMC). The partnership will help in harnessing data analytics and insights by developing and training a proprietary Stagwell large language model (LLM) purpose-built for Stagwell clients, productizing data assets via APIs to create new digital experiences for brands, and multiplying the value of their first-party data ecosystems to drive new revenue streams using Vertex AI and open source-based models., May 2023 - IBM launched a new AI and data platform, watsonx, it is aimed at allowing businesses to accelerate advanced AI usage with trusted data, speed and governance. IBM also introduced GPU-as-a-service, which is designed to support AI intensive workloads, with an AI dashboard to measure, track and help report on cloud carbon emissions. With watsonx, IBM offers an AI development studio with access to IBMcurated and trained foundation models and open-source models, access to a data store to gather and clean up training and tune data,. Key drivers for this market are: Rapid Increase in Big Data, Emerging Promising Use Cases of Data Science and Machine Learning; Shift of Organizations Toward Data-intensive Approach and Decisions. Potential restraints include: Rapid Increase in Big Data, Emerging Promising Use Cases of Data Science and Machine Learning; Shift of Organizations Toward Data-intensive Approach and Decisions. Notable trends are: Small and Medium Enterprises to Witness Major Growth.

Amazon Data Services Inc Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

This dataset contains customer reviews from the Amazon Commerce dataset. The original data was provided in ARFF format and included mixed or improperly encoded values.

I cleaned and converted it into a clean CSV file, fixing encoding issues (UTF-8), removing extra symbols, and organizing columns for better readability and usability.