The Registry of Open Data on AWS contains publicly available datasets that are available for access from AWS resources. Note that datasets in this registry are available via AWS resources, but they are not provided by AWS; these datasets are owned and maintained by a variety of government organizations, researchers, businesses, and individuals. This dataset contains derived forms of the data in https://github.com/awslabs/open-data-registry that have been transformed for ease of use with machine interfaces. Currently, only the ndjson form of the registry is populated here.

Prices are current as of 7/05/11.1CPUs are in terms of a 1-GHz Opteron 2007 processor, unless otherwise noted. For example, a machine with four 1-GHz processors would be listed as 4×1.1aCPU is a quad-core Xeon X5570, i.e., two quad-core CPUs, where each core is 4.19 GHz.1bCPU is a quad-core Xeon X5570, and instance includes two NVIDIA Tesla "Fermi" M2050 GPUs.2Costs reflect standard EC2 use with Linux OS. Costs increase when using Windows and decrease when using Reserved Instances (up-front payment) or Spot Instances (user-specified price on unused EC2 capacity).3Within same AWS availability region (e.g., AWS US-East).4Request costs are more difficult to estimate, and are usually more pertinent when databases and other similar services are involved. Programs like IOSTAT can be used to estimate EBS requests.

The Data Exchange Platform Services market is experiencing robust growth, driven by the increasing need for secure and efficient data sharing across organizations. The market, estimated at $15 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. The rise of cloud computing and the increasing adoption of APIs are simplifying data exchange processes and reducing costs, making data exchange platforms more accessible to businesses of all sizes. Furthermore, stringent data privacy regulations, such as GDPR and CCPA, are driving the demand for secure and compliant data exchange solutions. The growing importance of data analytics and the need for real-time data insights across different systems also contribute significantly to market growth. Major players like Amazon Web Services, Microsoft, and IBM are actively investing in and expanding their data exchange platform offerings, further fueling market competition and innovation. The market is segmented by deployment (cloud, on-premises), organization size (small, medium, large), and industry vertical (healthcare, finance, retail, etc.). The cloud deployment segment is expected to dominate due to its scalability, flexibility, and cost-effectiveness. The increasing adoption of data exchange platforms in the healthcare and finance sectors, driven by the need for secure patient data sharing and financial transactions, is also significantly contributing to market growth. However, challenges remain, including concerns over data security and integration complexities, which can act as restraints to market expansion. Overcoming these challenges through robust security protocols and user-friendly interfaces will be crucial for sustained market growth. The competitive landscape is characterized by the presence of established technology giants and specialized data exchange platform providers. This intense competition fosters innovation and drives down prices, ultimately benefiting end-users.

The Data Exchange Tool market is booming, projected to reach $20B+ by 2033 (CAGR 18%). This in-depth analysis explores market drivers, trends, restraints, key players (Snowflake, Informatica, AWS, etc.), and regional growth. Learn about secure data sharing solutions and the future of data exchange.

The Data Exchange Platform Services Marketsize was valued at USD 1.3 billion in 2023 and is projected to reach USD 7.5 billion by 2032, exhibiting a CAGR of 19.15 % during the forecast period. Recent developments include: November 2019: Amazon Web Services (AWS) partnered with Deloitte to help customers securely find, subscribe to, and use third-party data in the cloud using AWS Data Exchange, a new service that can help address unique healthcare issues. March 2020: Google Cloud Platform (GCP) launched Anthos, a new platform that enables businesses to run their applications across multiple clouds and on-premises environments. Anthos includes a data exchange feature that allows businesses to share data between their applications, regardless of where they are deployed.. Key drivers for this market are: Increasing Adoption of Cloud-based Managed Services to Drive Market Growth. Potential restraints include: Misuse of Virtual Currency and Security Attacks Confines the Adoption of Cryptocurrencies. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

Discover the booming Data Marketplace Platform market! This in-depth analysis reveals market size, CAGR, key drivers, trends, and leading companies like AWS, Snowflake, and Acxiom. Learn about the future of data monetization and the opportunities within this rapidly expanding sector. Explore regional market shares and forecast projections for 2025-2033.

Amazon (AMZN) Stock Price Time-Series Dataset: May 2012 - November 2012

Dataset Overview

This dataset provides a detailed, intraday view of Amazon's stock (AMZN) price movements from May 21, 2012, to November 14, 2012. Meticulously compiled, it offers a granular perspective on market dynamics, enabling robust quantitative analysis and modeling.

Content

The dataset encompasses the following key financial metrics for each trading day:

• Date: The specific date of the trading session.
• Open: The initial price at the commencement of trading.
• High: The maximum price attained during the trading day.
• Low: The minimum price recorded during the trading day.
• Close: The final trading price at the market's close.
• Adj Close: The closing price adjusted for corporate actions like dividends and stock splits, providing a true return on investment.
• Volume: The number of shares exchanged throughout the trading day, indicating market activity and liquidity.

Intended Use Cases

This dataset is tailored for sophisticated financial analysis, model development, and academic research. Potential applications include:

• Algorithmic Trading Strategy Development: Design and back-test trading algorithms using historical price movements and volume data.
• Volatility Modeling: Analyze and forecast stock price volatility using time-series analysis techniques (e.g., GARCH models).
• Financial Forecasting: Implement machine learning models to predict future stock prices based on historical patterns.
• Event Study Analysis: Examine the impact of specific events or news announcements on Amazon's stock price.
• Risk Management: Evaluate potential risks associated with investing in Amazon stock during this period.
• Academic Research: Conduct studies on market efficiency, price discovery, and the impact of market microstructure on stock behavior.

Data Considerations

• Time Zone: Data is timestamped with Eastern Time (ET).
• Data Cleaning: The dataset has been verified for accuracy, but users are encouraged to perform their own data quality checks.

Contect info:

You can contect me for more data sets if you want any type of data to scrape

-E_mail

-Linkdin

-Kaggle

-X

-Github

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.

The AWS Public Blockchain Data initiative provides free access to blockchain datasets through collaboration with data providers. The data is optimized for analytics by being transformed into compressed Parquet files, partitioned by date for efficient querying.

Datasets

Blockchain dataset - Maintained by - Path:
- Bitcoin - AWS - s3://aws-public-blockchain/v1.0/btc/
- Ethereum - AWS - s3://aws-public-blockchain/v1.0/eth/
- Arbitrum - SonarX - s3://aws-public-blockchain/v1.1/sonarx/arbitrum/
- Aptos - SonarX - s3://aws-public-blockchain/v1.1/sonarx/aptos/
- Base - SonarX - s3://aws-public-blockchain/v1.1/sonarx/base/
- Provenance - SonarX - s3://aws-public-blockchain/v1.1/sonarx/provenance/
- XRP Ledger - SonarX - s3://aws-public-blockchain/v1.1/sonarx/xrp/
- Stellar(XDR files) - Stellar - s3://aws-public-blockchain/v1.1/stellar/
- The Open Network (TON) - TON - s3://aws-public-blockchain/v1.1/ton/
- Cronos - Cronos - s3://aws-public-blockchain/v1.1/cronos/

Become a Data Provider

We welcome additional blockchain data providers to join this initiative. If you're interested in contributing datasets to the AWS Public Blockchain Data program, please contact our team at aws-public-blockchain@amazon.com.

Amazon reported $88.67B in Cost of Sales for its fiscal quarter ending in September of 2025. Data for Amazon | AMZN - Cost Of Sales including historical, tables and charts were last updated by Trading Economics this last December in 2025.

Amazon reported $41.49B in Stock for its fiscal quarter ending in September of 2025. Data for Amazon | AMZN - Stock including historical, tables and charts were last updated by Trading Economics this last December in 2025.

The High-Speed Data Transfer System market is booming, projected to reach $117.25 billion by 2033 with a 15% CAGR. Learn about key market drivers, trends, and leading companies shaping this rapidly evolving sector. Explore regional market shares and growth projections for cloud-based and on-premise solutions across BFSI, media, and other industries.

The Sentinel-2 mission is a land monitoring constellation of two satellites that provide high resolution optical imagery and provide continuity for the current SPOT and Landsat missions. The mission provides a global coverage of the Earth's land surface every 5 days, making the data of great use in on-going studies. L1C data are available from June 2015 globally. L2A data are available from November 2016 over Europe region and globally since January 2017.

This dataset can be used to test Minimal Viable Product 2 from Research Data Exchange. This means that the data can only be analyzed in a closed and secure environment and that the output will be checked before it is shared with the data requester. The link to access the data can be found in the references. The data contains customer sentiments regarding Baby products purchased on Amazon.com, on the basis of their written reviews. The data is used for an assignment from the master track Behavioural Data Science, which be found on Kaggle, see reference.

Dataset Description This dataset contains historical stock price data across multiple timeframes, ranging from intraday to higher timeframes. The available timeframes include:

1-minute (1m) 5-minute (5m) 30-minute (30m) 60-minute (1h) 240-minute (4h) Daily (1D) Weekly (1W) Monthly (1M)

Each dataset file represents price movements at a specific timeframe, enabling traders and analysts to perform technical analysis across different granularities.

Columns - datetime: The timestamp or date of the recorded price data. - open: The opening price at the beginning of the timeframe. - high: The highest price reached within the timeframe. - low: The lowest price reached within the timeframe. - close: The closing price at the end of the timeframe. - % change: The percentage change in price from the previous timeframe, indicating the rate of price movement.

Exchange Information The dataset is sourced from the IC Market exchange, ensuring reliable and up-to-date market data. https://in.tradingview.com/broker/ICmarkets/

Time Period Covered The dataset spans from the inception of the company to 2025, covering complete historical stock price data.

Potential Use Cases - Technical analysis: Identifying trends, support/resistance levels, and chart patterns. - Algorithmic trading: Backtesting strategies across multiple timeframes. - Machine learning models: Training predictive models for stock price movements. - Volatility analysis: Understanding market behavior across different timeframes.

This data is provided as a supplement to NIST Technical Note 2140, AWS-3 LTE Impacts on AMT, which presents test results assessing the impact of adjacent-band long term evolution (LTE) emissions on aeronautical mobile telemetry (AMT) systems. The data provided here is sufficient to reproduce all of the plots and analyses in Chapters 5 and 6, and Appendices B, C, D, and E, which present the data analysis results. All files are spreadsheets in comma-separated values (CSV) format, with labeled columns for various key performance indicators (KPIs) and test configurations. See the data description document provided in the zip file for an outline of the contents and the technical note referenced above for details on the data collection.

This dataset contains historical stock price data for Amazon from their initial public offering on the stock exchange until the current time. Data includes daily opening prices, closing prices, high and low prices, trading volumes and adjusted closing prices.

The Real-time Data Transfer Service market is booming, projected to reach $15 billion in 2025 with an 18% CAGR through 2033. Discover key trends, drivers, and regional insights in this comprehensive market analysis. Explore leading companies and applications across sectors like healthcare, manufacturing, and finance.

Amazon reported $727.92B in Assets for its fiscal quarter ending in September of 2025. Data for Amazon | AMZN - Assets including historical, tables and charts were last updated by Trading Economics this last December in 2025.

Amazon reported $50.74B in Selling and Administration Expenses for its fiscal quarter ending in September of 2025. Data for Amazon | AMZN - Selling And Administration Expenses including historical, tables and charts were last updated by Trading Economics this last December in 2025.