In March 2025, a total of 346 database solutions were available to customers on the Google Cloud Platform (GCP) marketplace. Most tools belonged to the virtual machines type, with 149 tools, followed by the software as a service (SaaS) and APIs type, with 127.

Business Listings Database is the source of point-of-interest data and can provide you with all the information you need to analyze how specific places are used, what kinds of audiences they attract, and how their visitor profile changes over time.

The full fields description may be found on this page: https://docs.dataforseo.com/v3/databases/business_listings/?bash

You can check the fields description in the documentation: current Full database: https://docs.dataforseo.com/v3/databases/google/full/?bash; Historical Full database: https://docs.dataforseo.com/v3/databases/google/history/full/?bash.

Full Google Database is a combination of the Advanced Google SERP Database and Google Keyword Database.

Google SERP Database offers millions of SERPs collected in 67 regions with most of Google’s advanced SERP features, including featured snippets, knowledge graphs, people also ask sections, top stories, and more.

Google Keyword Database encompasses billions of search terms enriched with related Google Ads data: search volume trends, CPC, competition, and more.

This database is available in JSON format only.

You don’t have to download fresh data dumps in JSON – we can deliver data straight to your storage or database. We send terrabytes of data to dozens of customers every month using Amazon S3, Google Cloud Storage, Microsoft Azure Blob, Eleasticsearch, and Google Big Query. Let us know if you’d like to get your data to any other storage or database.

Google searches of sensitive terms

You can check the fields description in the documentation: regular SERP: https://docs.dataforseo.com/v3/databases/google/serp_regular/?bash; Advanced SERP: https://docs.dataforseo.com/v3/databases/google/serp_advanced/?bash; Historical SERP: https://docs.dataforseo.com/v3/databases/google/history/serp_advanced/?bash You don’t have to download fresh data dumps in JSON or CSV – we can deliver data straight to your storage or database. We send terrabytes of data to dozens of customers every month using Amazon S3, Google Cloud Storage, Microsoft Azure Blob, Eleasticsearch, and Google Big Query. Let us know if you’d like to get your data to any other storage or database.

You can check the fields description in the documentation: current Keyword database: https://docs.dataforseo.com/v3/databases/google/keywords/?bash; Historical Keyword database: https://docs.dataforseo.com/v3/databases/google/history/keywords/?bash. You don’t have to download fresh data dumps in JSON or CSV – we can deliver data straight to your storage or database. We send terrabytes of data to dozens of customers every month using Amazon S3, Google Cloud Storage, Microsoft Azure Blob, Eleasticsearch, and Google Big Query. Let us know if you’d like to get your data to any other storage or database.

United States Google Search Trends: Government Measures: Government Subsidy data was reported at 0.000 Score in 06 Mar 2025. This stayed constant from the previous number of 0.000 Score for 05 Mar 2025. United States Google Search Trends: Government Measures: Government Subsidy data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 06 Mar 2025, with 1192 observations. The data reached an all-time high of 0.000 Score in 06 Mar 2025 and a record low of 0.000 Score in 06 Mar 2025. United States Google Search Trends: Government Measures: Government Subsidy data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s United States – Table US.Google.GT: Google Search Trends: by Categories.

The Global Power Plant Database is a comprehensive, open source database of power plants around the world. It centralizes power plant data to make it easier to navigate, compare and draw insights. Each power plant is geolocated and entries contain information on plant capacity, generation, ownership, and fuel type. As …

The Database Migration Solutions market is experiencing robust growth, driven by the increasing adoption of cloud computing, the need for data modernization, and the rising demand for improved data management capabilities across diverse sectors. 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 an estimated market value of $45 billion by 2033. This growth is fueled by several key factors, including the expanding adoption of cloud-native applications requiring seamless data migration, the growing prevalence of hybrid cloud environments mandating efficient data transfer, and the stringent regulatory requirements driving data security and compliance upgrades. Significant investments in digital transformation initiatives by enterprises across various industries, including finance, government, and telecommunications, are further accelerating market expansion. The market segmentation reveals a strong preference for live migration solutions over backup migration, reflecting a growing need for minimal downtime during database transitions. Geographically, North America currently holds the largest market share, followed by Europe and Asia-Pacific. However, the Asia-Pacific region is projected to exhibit the fastest growth rate during the forecast period due to increasing digitalization and cloud adoption in developing economies like India and China. Competitive pressures are intense, with major cloud providers like AWS, Google Cloud, and Azure, as well as specialized migration solution vendors, vying for market share. Despite the overall positive outlook, challenges such as data security concerns, the complexity of migration processes, and the potential for disruptions during migration remain significant restraints. The market is poised for continued expansion, driven by technological innovation and the ever-increasing reliance on efficient data management.

description:

GRIN-Global (GG) is a database application that enables genebanks to store and manage information associated with plant genetic resources (germplasm) and deliver that information globally. The GRIN-Global project's mission is to provide a scalable version of the Germplasm Resource Information Network (GRIN) suitable for use by any interested genebank in the world. The GRIN-Global database platform has been and is being implemented at various genebanks around the world. The first version, 1.0.7, was released in December, 2011 in a joint effort by the Global Crop Diversity Trust, Bioversity International, and the Agricultural Research Service of the USDA. The U.S. National Plant Germplasm System version (1.9.4.2) entered into production on November 30, 2015.

Typically set up in a networked environment, GG can also run stand-alone on a single personal computer. GG has been developed with open source software and its source code is available, and Genebanks can thus tailor GG to meet their specific requirements. GG comprises a suite of programs, including a Curator Tool, Updater, Search Tool, Admin Tool, and Public Website with Shopping Cart. Through the Public Website, researchers can access germplasm information; search the entire GG database and download results; and order germplasm from the genebank. Data are also associated with Google Maps.

Current installations include Bolivia (INIAF), Chile (INIA), CIMMYT (CGIAR), Czech Republic (Crop Research Institute), Portugal (INIAV), USDA (NPGS), Tunisia (BNG), CIP (CGIAR), Genetic Resources of Madeira Island (Portugal), CIAT (CGIAR) with many others under evaluation.

GRIN-Global (GG) is a database application that enables genebanks to store and manage information associated with plant genetic resources (germplasm) and deliver that information globally. The GRIN-Global project's mission is to provide a scalable version of the Germplasm Resource Information Network (GRIN) suitable for use by any interested genebank in the world. The GRIN-Global database platform has been and is being implemented at various genebanks around the world. The first version, 1.0.7, was released in December, 2011 in a joint effort by the Global Crop Diversity Trust, Bioversity International, and the Agricultural Research Service of the USDA. The U.S. National Plant Germplasm System version (1.9.4.2) entered into production on November 30, 2015.

Typically set up in a networked environment, GG can also run stand-alone on a single personal computer. GG has been developed with open source software and its source code is available, and Genebanks can thus tailor GG to meet their specific requirements. GG comprises a suite of programs, including a Curator Tool, Updater, Search Tool, Admin Tool, and Public Website with Shopping Cart. Through the Public Website, researchers can access germplasm information; search the entire GG database and download results; and order germplasm from the genebank. Data are also associated with Google Maps.

Current installations include Bolivia (INIAF), Chile (INIA), CIMMYT (CGIAR), Czech Republic (Crop Research Institute), Portugal (INIAV), USDA (NPGS), Tunisia (BNG), CIP (CGIAR), Genetic Resources of Madeira Island (Portugal), CIAT (CGIAR) with many others under evaluation.

Google, Inc. Whois Database, discover comprehensive ownership details, registration dates, and more for Google, Inc. with Whois Data Center.

The datasets include all analyzed Google Trends data on climate change and COVID-19 data for publication.

Google Search Trends: Online Training: Udemy data was reported at 7.000 Score in 20 Mar 2025. This records an increase from the previous number of 0.000 Score for 19 Mar 2025. Google Search Trends: Online Training: Udemy data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 20 Mar 2025, with 1206 observations. The data reached an all-time high of 100.000 Score in 10 Aug 2024 and a record low of 0.000 Score in 19 Mar 2025. Google Search Trends: Online Training: Udemy data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Laos – Table LA.Google.GT: Google Search Trends: by Categories.

Explore our expansive keyword database, housing 7.2 billion keywords across 229 countries, alongside detailed SERP results. Discover insights into search volume, keyword difficulty, CPC, competition, special search elements, and social domains.

Our database offers flexibility, available for purchase as the entire dataset or customizable subsets. With regular refreshes and a polishing option before sharing, ensure you're equipped with the most accurate and up-to-date information for informed decision-making and strategic planning in SEO and marketing endeavours.

The Global Flood Database contains maps of the extent and temporal distribution of 913 flood events occurring between 2000-2018. For more information, see the associated journal article. Flood events were collected from the Dartmouth Flood Observatory and used to collect MODIS imagery. The selected 913 events are those that were successfully mapped (passed quality control as having significant inundation beyond permanent water) using 12,719 scenes from Terra and Aqua MODIS sensors. Each pixel was classified as water or non-water at 250-meter resolution during the full date range of each flood event and subsequent data products were generated including maximum flood extent ("flooded" band) and the duration of inundation in days ("duration" band). Water and non-water classifications during a flood event include permanent water (here resampling the 30-meter JRC Global Surface Water dataset representing permanent water to 250-meter resolution), which can be masked out to isolate flood water using the "jrc_perm_water" band. Extra data quality bands were added representing cloud conditions during the flood event (e.g., "clear_views" representing the number of clear days the flood was observed between its start and end dates and "clear_perc" representing the percentage of clear day observation of the total event duration in days). Each image in the ImageCollection represents the map of an individual flood. The collection can be filtered by date, country, or Dartmouth Flood Observatory original ID.

The World Database on Protected Areas (WDPA) is the most up-to-date and complete source of information on protected areas, updated monthly with submissions from governments, non-governmental organizations, landowners, and communities. It is managed by the United Nations Environment Programme's World Conservation Monitoring Centre (UNEP-WCMC) with support from IUCN and its …

This data compiles the toxicity data on stygofauna and other aquatic subterranean organisms in one (eco)toxicological database. A total of 46 studies were found, containing 472 toxic endpoints covering 43 different stressors. These compounds were tested on subterranean organisms from four phyla, 12 orders, 24 genera, and 55 species. The studies included were published between 1976 and July of 2023, in 13 different countries. The suitability of the studies was assessed in order to indicate the completeness of reporting and their suitability for use in hazard and risk assessment. This compilation provides a valuable source of data for future development of toxicity testing protocols for groundwater organisms, and to support decision-making, ecological risk assessments and the derivation of water quality criteria for the protection of groundwater ecosystems. The database will be updated regularly.

The database was founded on literature searches using Google Scholar, Web of Science and Scopus, reference lists of the scientific/peer reviewed literature, as well as generic internet searches. An example of the search criteria used in Scopus can be seen below.

· “Stygofauna” OR “Stygo” OR “Hypogean” OR “Groundwater organism” OR “Groundwater invertebrate” OR “Stygobite”

o AND

· “Toxicity” OR “Ecotoxicity” OR “Dose-response” OR “Sensitivity”

Searches were conducted in English and identified several studies written in German and French that had English abstracts or keywords. Studies in languages other than English were translated using Google translate. The current database (version 2023.12) includes papers published prior to December 2023. The criteria for the inclusion of data from a study into the database was the availability of one of the following toxicity endpoints: Lethal concentration (LC), Effect concentration (EC), Inhibition concentration (IC), Lethal temperature (Ltemp), Effect temperature (Etemp), Lethal time (Ltime), Effect time (Etime), No observable effect concentration (NOEC), and Lowest observed effect concentration” (LOEC). Where available, the effect of the EC is mentioned.

The Cloud Database Management Systems (DBMS) market is experiencing robust growth, driven by the increasing adoption of cloud computing across various sectors. The market, estimated at $80 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, the inherent scalability and cost-effectiveness of cloud-based solutions are attracting businesses of all sizes, from startups to large enterprises. Secondly, the rising need for data-driven decision-making is propelling demand for efficient and reliable database management systems capable of handling massive volumes of data. Thirdly, advancements in technologies like serverless computing and AI/ML integration are enhancing the capabilities of cloud DBMS, further accelerating market growth. The market is segmented by deployment type (Multi-Cloud, Intercloud, Distributed Cloud, Others) and application (Retail, Manufacturing, Healthcare, Finance, Others), with multi-cloud deployments and applications in retail and finance leading the way. Major players such as Amazon, Microsoft, Google, and Oracle dominate the market, but emerging players are also gaining traction, fostering competition and innovation. Geographic distribution reflects the global adoption of cloud technologies, with North America and Europe holding significant market shares, while the Asia-Pacific region is poised for substantial growth in the coming years. The restraints on market growth are primarily related to security concerns surrounding data breaches and compliance issues. However, robust security measures implemented by cloud providers and evolving regulatory frameworks are mitigating these concerns. Another restraint is the complexity associated with migrating existing on-premise databases to the cloud, which can require significant investment in time and resources. Despite these challenges, the long-term outlook for the Cloud DBMS market remains exceptionally positive, driven by the continued adoption of digital transformation initiatives across industries globally and the growing preference for flexible, scalable, and cost-effective data management solutions. The forecast period indicates continuous expansion, with the market expected to reach a substantial size by 2033, representing significant opportunities for both established players and new entrants.

This dataset provides the locations of oil and gas (O&G) related infrastructure globally. The Oil and Gas Infrastructure Mapping (OGIM) database is a project developed by the Environmental Defense Fund (EDF) and MethaneSAT LLC, a wholly-owned subsidiary of EDF. The primary objective of developing a standardized O&G infrastructure database such …