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.

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 NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four "Tier 1" greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). The CMIP6 GCM runs were developed in support of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). This dataset includes downscaled projections from ScenarioMIP model runs for which daily scenarios were produced and distributed through the Earth System Grid Federation. The purpose of this dataset is to provide a set of global, high resolution, bias-corrected climate change projections that can be used to evaluate climate change impacts on processes that are sensitive to finer-scale climate gradients and the effects of local topography on climate conditions.

Automated Weather Station and AWS-like networks are the primary source of surface-level meteorological data in remote polar regions. These networks have developed organically and independently, and deliver data to researchers in idiosyncratic ASCII formats that hinder automated processing and intercomparison among networks. Moreover, station tilt causes significant biases in polar AWS measurements of radiation and wind direction. Researchers, network operators, and data centers would benefit from AWS-like data in a common format, amenable to automated analysis, and adjusted for known biases. This project addresses these needs by developing a scientific software workflow called "Justified AWS" (JAWS) to ingest Level 2 (L2) data in the multiple formats now distributed, harmonize it into a common format, and deliver value-added Level 3 (L3) output suitable for distribution by the network operator, analysis by the researcher, and curation by the data center. Polar climate researchers currently face daunting problems including how to easily: 1. Automate analysis (subsetting, statistics, unit conversion) of AWS-like L2 ASCII data. 2. Combine or intercompare data and data quality from among unharmonized L2 datasets. 3. Adjust L2 data for biases such as AWS tilt angle and direction. JAWS addresses these common issues by harmonizing AWS L2 data into a common format, and applying accepted methods to quantify quality and estimate biases. Specifically, JAWS enables users and network operators to 1. Convert L2 data (usually ASCII tables) into a netCDF-based L3 format compliant with metadata conventions (Climate-Forecast and ACDD) that promote automated discovery and analysis. 2. Include value-added L3 features like the Retrospective, Iterative, Geometry-Based (RIGB) tilt angle and direction corrections, solar angles, and standardized quality flags. 3. Provide a scriptable API to extend the initial L2-to-L3 conversion to newer AWS-like networks and instruments. Polar AWS network experts and NSIDC DAAC personnel, each with decades of experience, will help guide and deliberate the L3 conventions implemented in Stages 2-3. The project will start on July 1, 2017 at entry Technology Readiness Level 3 and will exit on June 30, 2019 at TRL 6. JAWS is now a heterogeneous collection of scripts and methods developed and validated at UCI over the past 15 years. At exit, JAWS will comprise three modular stages written in or wrapped by Python, installable by Conda: Stage 1 ingests and translates L2 data into netCDF. Stage 2 annotates the netCDF with CF and ACDD metadata. Stage 3 derives value-added scientific and quality information. The labor-intensive tasks include turning our heterogeneous workflow into a robust, standards-compliant, extensible workflow with an API based on best practices of modern scientific information systems and services. Implementation of Stages 1-2 may be straightforward though tedious due to the menagerie of L2 formats, instruments, and assumptions. The RIGB component of Stage 3 requires ongoing assimilation of ancillary NASA data (CERES, AIRS) and use of automated data transfer protocols (DAP, THREDDS). The immediate target recipient elements are polar AWS network managers, users, and data distributors. L2 borehole data suffers from similar interoperability issues, as does non-polar AWS data. Hence our L3 format will be extensible to global AWS and permafrost networks. JAWS will increase in situ data accessibility and utility, and enable new derived products (both are AIST goals). The PI is a long-standing researcher, open source software developer, and educator who understands obstacles to harmonizing disparate datasets with NASA interoperability recommendations. Our team participates in relevant geoscience communities, including ESDS working groups, ESIP, AGU, and EarthCube.

These datasets contain peer-to-peer trades from various recommendation platforms.

Metadata includes

• peer-to-peer trades

• have and want lists

• image data (tradesy)

This data set provides measurements of carbon dioxide flux rates (FCO2), gas transfer velocity (k), and partial pressures (pCO2) at 75 sites on rivers and streams of the Amazon River system in South America for the period beginning July 1, 2004, and ending January 23, 2007. Several fieldwork campaigns occurred between June 2004 and January 2007 in the Amazon River basin, with discharge conditions ranging from low to high flow. The sampled areas span the spectrum of chemical characteristics observed across the entire basin, including, for example, both low and high pH values and suspended sediment loads. There is one comma-delimited data file in this data set.

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.

In 2024, with a market share of ** percent, Amazon Web Services (AWS) is set to be the leading global infrastructure as a service (IaaS) and platform as a service (PaaS) hyperscale vendor. In this specific instance, the four hyperscalers are characterized by their technology, CAPEX budget, resources, heft, and customer momentum that make them unique. While there are other companies in the market, the hyperscalers outperform these companies under consideration of the aforementioned metrics. Hyperscaler cloud provider Hyperscale cloud providers have global scale, innovative technology, and deep expertise in consulting and global business solutions. The companies utilize these abilities to offer a broad range of services to their customers, including platform re-architecture, data migration, and application development. In doing this, they become business partners rather than being mere suppliers of cloud computing resources. Cloud market segments Cloud computing can be compartmentalized into software as a service (SaaS), PaaS, and IaaS. SaaS is a software delivery model in which software is centrally hosted and delivered to customers on a subscription basis. IaaS offers an entire information technology (IT) infrastructure to its customers, which is provisioned and managed over the internet. PaaS, on the other hand, provides a full development and deployment environment in the cloud.

Market Analysis for Amazon AWS Cloud Solutions The market for Amazon AWS (Amazon Web Services) Cloud Solutions is projected to reach a staggering $473.30 million by 2033, growing at a remarkable CAGR due to the increasing adoption of cloud computing and the expansion of data-intensive applications. Key drivers fueling this growth include the cost efficiency, flexibility, and scalability offered by cloud platforms. The market is segmented by type (Infrastructure Setup, Application Development, Platform, Other) and application (Large Corporations, SMEs). The AWS cloud solutions market is dominated by established players such as Netguru SA, Logicalis, and Rackspace. These companies offer a comprehensive suite of services, ranging from consulting and design to implementation and support. The market is expected to witness increased competition from emerging cloud providers in the coming years. Geographical expansion is another key trend, with the market witnessing significant growth in emerging regions such as Asia-Pacific and the Middle East & Africa.

This data set provides continental-scale hydrological river flow routing parameter data for the Amazon and Tocantins River basins at 5 minute (~9 km) resolution (Costa et al., 2002). The data set includes four geospatial data files (in standard ESRI Arc/Info ASCII Grid format): (1) the river network (flow direction); (2) sinuosity of each of the main rivers, measured at 111 river sections in the basins; (3) depth to the water table; and (4) transmissivity of the aquifer. The latter two parameters were derived from measurements taken at 81 wells located throughout the basins. There is also a compressed file (*.zip) which contains the time series of monthly mean river discharge and long-term climatology (monthly mean) for the period of record at each of 122 fluviometric stations located throughout the basin. These files are provided in ASCII common-separated (.csv) format. Also included in this data set are two data files in *.csv format; one containing river discharge station location and drainage area information and one containing original well data.

The Data Catalog Marketsize was valued at USD 878.8 USD million in 2023 and is projected to reach USD 2749.95 USD million by 2032, exhibiting a CAGR of 17.7 % during the forecast period. Data catalog is another concept that is used to refer to a unified list of all the data resources within an organization and their descriptions that are crucial in the course of data search. It can also sort data, effectively making it easier to find and use data sets that the user requires. based on their usage, data catalogs can be distinguished into business, technical, and operation catalogs; business use for business intelligence, technical for providing metadata for technical use, and operational use for tracking operational data. Some of the significant elements of data catalogs are data lineage, metadata management, search and discovery features, data governance, and collaboration. They are actively utilized in industries for increasing data quality, satisfying the requirements of compliance, and optimizing the analysis to support better decision-making and increase efficiency in business operations. Recent developments include: February 2024 – Collibra launched Collibra AI Governance, built on their Data Intelligence Platform, enabling organizations to deliver trusted AI effectively through the use of Collibra Data Catalog. It aided teams in collaborating for compliance, improved model performance, reduced risk, and led to faster production timelines., September 2023 – AWS Lake Formation launched a Hybrid Access Module for the AWS Glue Data Catalog, allowing users to selectively enable Lake Formation for tables and databases without interrupting existing users or workloads. This feature provided flexibility and an integral path for enabling Lake Formation, reducing the need for coordination among owners and consumers., July 2023 – Teradata acquired Stemma Technologies to enhance its analytics capabilities, particularly in data discovery and delivery. Stemma’s automated data catalog bolstered Teradata’s offerings, aiming to improve user experience and accelerate ML and AI analytics growth., June 2023 – Acryl Data secured USD 21 million in Series A funding led by 8VC to enhance its open-source data catalog platform. This investment enhanced their cloud offerings and expanded their vision towards a data control plane., May 2023 – data.world launched its new Data Catalog Platform, integrating generative AI bots to enhance data discovery. With over 2 million users, the platform aimed to make data discovery and knowledge unlocking accessible to users of all expertise levels., February 2023 – data.world, a data governance platform, launched the first AI Lab for the data catalog industry. This Artificial Intelligence (AI) Lab would be important in bringing partners and customers together to enhance data team productivity using AI technology., November 2022 – Amazon Web Services (AWS) launched DataZone, a new machine learning-based data management service to help enterprises catalog, share, govern, and discover their data quickly.. Key drivers for this market are: Exponential Growth of Data Volume and Data Analytics to Fuel Market Growth. Potential restraints include: High Initial Deployment Cost and Privacy Concerns to Hinder Market Growth. Notable trends are: Growing Adoption of AI and Automation Technologies to Amplify Market Growth.

This data set includes Landsat TM scenes from across the Legal Amazon region. A single image is provided for each spatial tile, representing the most cloud-free retrieval from 9/21/86 to 9/17/94. All files are in a single directory, including one band-sequential (bsq) file and one database (ddr) file for each scene.

Global, aggregated physical air quality data from public data sources provided by government, research-grade and other sources. These awesome groups do the hard work of measuring these data and publicly sharing them, and our community makes them more universally-accessible to both humans and machines.

Recent developments include: April 2023: IBM Corporation announced the launch of a new QRadar Security Suite to accelerate threat detection and response. The launch of the new technology will help improve the productivity of security teams by enabling analysts to respond faster and more efficiently, thereby freeing them up for higher-value work., December 2022: Microsoft and LSEG (London Stock Exchange Group) announced a partnership to use Microsoft Cloud to create the latter’s data infrastructure and develop new data & analytics products and services. This partnership would strengthen its position as the world's leading financial market infrastructure and data provider., November 2022: Dremio, a simple and open data lakehouse, announced key features for updating & writing data, improved support for semi-structured data, and expanded data ecosystem and business intelligence (BI) integrations in the data lakehouse evolution., February 2022: Persistent Systems acquired Data Glove and created a new Microsoft business unit focused on the Azure cloud. The acquisition expanded the delivery capabilities with highly skilled personnel, established a new nearshore distribution center in Costa Rica, and expanded the company's presence in India and the U.S., December 2021: Informatica launched a new solution that democratized access to cloud data lakes on Amazon Web Services (AWS) with AWS Lake Formation. This solution enabled business users at every level within an organization to access their data with improved security and trust to make informed business decisions.. Key drivers for this market are: Rising Demand for Effective Security Solutions Among Organizations to Drive Market Growth. Potential restraints include: Budgetary Issues Among Small-Scale Businesses May Hinder Market Growth. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

The global market for Amazon AWS cloud solutions, while not explicitly stated in the provided data, can be reasonably estimated based on the overall cloud market size and Amazon's dominant market share. Considering a global cloud market size of $371 billion (in 2025) and a 3.3% CAGR, and assuming Amazon Web Services (AWS) holds approximately a 32% market share (a figure consistently reported in industry analyses), the AWS market segment in 2025 is estimated at $118.72 billion. This significant market dominance is driven by factors including AWS's extensive service portfolio, robust infrastructure, global reach, strong developer community, and continuous innovation. The market is segmented by application (large corporations and SMEs) and service type (cloud infrastructure setup, cloud application development services, and cloud platform), reflecting the diverse needs of businesses adopting cloud technologies. Key trends shaping this market include the increasing adoption of serverless computing, the rise of artificial intelligence (AI) and machine learning (ML) applications in the cloud, and the growing demand for enhanced security and compliance features. Restraints on market growth could include concerns regarding data privacy, vendor lock-in, and the complexity associated with migrating legacy systems to the cloud. The regional distribution likely mirrors the global cloud market, with North America and Europe holding substantial market share initially, followed by growth in Asia-Pacific and other regions as cloud adoption matures. The projected CAGR of 3.3% suggests a consistent, albeit moderate, growth trajectory for the AWS market throughout the forecast period (2025-2033). This growth will likely be fueled by continued digital transformation initiatives across industries, the expansion of cloud-native applications, and the increasing reliance on cloud-based infrastructure for business continuity and scalability. Competition from other major cloud providers will remain intense, but AWS's established position, extensive ecosystem, and continuous investments in research and development are likely to maintain its leading market share, even as the market expands. The long-term success of AWS will depend on its ability to address the evolving needs of its customers, adapting to new technologies and trends while maintaining a high level of security and reliability.

The amount of corporate data stored in the cloud has increased in recent years and is predicted to surpass ** percent by 2022. This is a significant rise from 2015 when only **% of corporate data was stored in the cloud. This trend is expected to continue in the future. What is driving the adoption of cloud technology? The global public cloud services market is expected to grow by approximately ** percent in 2023, which equates to around *** billion U.S. dollars. As businesses expand, their data storage and IT infrastructure needs become increasingly challenging to meet with on-premises storage servers and hardware alone. This growth creates a crucial need for scalability, which can only be efficiently and cost-effectively managed through cloud-based services. Additionally, companies are moving towards cloud technology to enhance their security, reliability, and business agility. The four major players in the cloud market Amazon, Google, Microsoft, and Alibaba are known as the big four in cloud technology, controlling over two-thirds of the global cloud market. Amazon Web Services (AWS) has held the majority of the market share for several years, with **% of the entire market. Microsoft is the closest competitor, growing its market share year on year. Its suite of Office products offered on the cloud for enterprises and consumers worldwide has contributed to their success.

According to estimates, Amazon claimed the top spot among online retailers in the United States in 2023, capturing 37.6 percent of the market. Second place was occupied by the e-commerce site of the retail chain Walmart, with a 6.4 percent market share, followed in third place by Apple, with 3.6 percent.

Amazon’s continued success

Amazon has long dominated the e-commerce market as the world’s favorite online marketplace. In 2022, company hit over half a trillion U.S. dollars in net sales. The United States is by far Amazon’s most profitable market, as the U.S. branch generated over 356 billion U.S. dollars in sales in 2022. Germany ranked second, with 33 billion dollars, followed closely by the United Kingdom with 30 billion dollars.

Online shopping on the rise

Online shopping has grown significantly over the past decade, with more people turning to the internet for their shopping needs. The proof is in the numbers: the U.S. e-commerce industry was worth almost a trillion dollars in 2023. By 2027, forecasts show that the online market will grow to more than 50 percent. U.S. online shoppers purchase fashion and food and beverages the most via the internet.

S-102 is a data and metadata encoding specification that is part of the S-100 Universal Hydrographic Data Model, an international standard for hydrographic data exchange. This collection of data contains bathymetric surfaces from NOAA/NOS/OCS National Bathymetric Source, for various U.S. coastal and offshore waters and the great lakes. These datasets are encoded as HDF5 files conforming to the S-102 specification.

This data set provides map images of hydrographic, morphologic, and edaphic features for the northern Amazon Basin in eastern Ecuador. The hydrographic data are available at two scales based on the 1:50,000 and 1:250,000-scale topographic source maps that were generated in 1990 and 1993, respectively. Morphological and edaphological data were digitized from a 1:500,000 map published in 1983. There are 3 compressed (*.zip) data files with this data set.

The global data center accelerator market is set to witness substantial growth, exhibiting a CAGR of 14.19% during the forecast period from 2025 to 2033, reaching a value of $11.29 million by 2033. This growth is primarily driven by the increasing adoption of cloud computing, artificial intelligence, and machine learning, which require high-performance computing capabilities. Key market drivers include the surge in data-intensive applications, the need for faster data processing, and the growing demand for energy-efficient solutions. Market trends include the shift towards specialized accelerators such as GPUs and FPGAs, the adoption of cloud-based accelerators, and the development of new accelerator technologies such as chiplets and neuromorphic computing. However, the market faces certain restraints, such as high costs, limited compatibility, and the challenge of integrating accelerators into existing systems. Major players in the market include Xilinx Inc (Advanced Micro Devices Inc), Achronix Semiconductor Corporation, IBM Corporation, NVIDIA Corporation, Cisco Systems Inc, Advanced Micro Devices Inc, Qualcomm Technologies Inc, NEC Corporation, Dell Technologies Inc, and Intel Corporation. Recent developments include: December 2022 - Atos has announced the development of a new solution in collaboration with AWS that allows clients to expedite and properly monitor company key performance indicators (KPIs) by offering simple access to SAP and non-SAP data silos. "Atos' AWS Data Lake Accelerator for SAP" is a new solution that delivers self-service and enterprise-wide reporting for significant insights into daily changes that swiftly influence choices to drive the bottom line., October 2022 - Accenture and Google Cloud announced an expansion of the global partnership, including a renewed commitment to growing their respective talent pools, expanding their joint capabilities, developing new data and AI solutions, and providing enhanced support to help clients build a solid digital core and reinvent their enterprises on the cloud., June 2022 - Sanofi has launched its first digital accelerator to help achieve its goal of being a premier digital healthcare company. The accelerator would create products and solutions to help Sanofi's objective of transforming medicine via the use of digital, data, and artificial intelligence (AI)., June 2022 - GE Digital announced the launch of its new accelerator product line, which includes software solutions to enable customers in asset-intensive energy industries quickly set up its Asset Performance Management (APM) and other services. GE Digital Accelerators are intended to accelerate time to value, extend APM to a wider variety of assets, and assist organizations in gaining financial benefit at their facilities and throughout the enterprise.. Key drivers for this market are: Increasing Deployment of AI in HPC Data Centers, Increasing Deployment of Data Center Facilities and Cloud-Based Services. Potential restraints include: Limited AI Hardware Experts Coupled with Infrastructural Concerns. Notable trends are: FPGA Processor Type Segemnt is Expected to Hold Significant Market Share.