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.

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.

Dataset

This dataset was created by Shreyashi Singh

Released under Database: Open Database, Contents: Database Contents

Contents

Fine-tune your SEO strategies using our daily-updated Whois database. Gain competitive insights to improve rankings and performance.

The Enterprise SEO Platforms market is experiencing robust growth, driven by the increasing reliance of businesses on digital channels for customer acquisition and brand building. The market size in 2025 is estimated at $5 billion, with a Compound Annual Growth Rate (CAGR) of 15% projected from 2025 to 2033. This growth is fueled by several key factors. Firstly, the ever-increasing complexity of search engine algorithms necessitates sophisticated SEO tools capable of managing large-scale website optimization efforts. Secondly, the rise of mobile-first indexing and the growing importance of voice search are forcing companies to adopt advanced SEO strategies, which in turn fuels demand for robust enterprise-grade platforms. Finally, the need for precise measurement and reporting of SEO performance is driving adoption of platforms that offer comprehensive analytics and data visualization capabilities. The market is segmented by platform type (navigational, transactional, informational) and user application (SMEs, large enterprises), with large enterprises representing a significant portion of the market due to their higher budgets and more complex SEO needs. The competitive landscape is highly dynamic, with established players like SEMrush and Ahrefs alongside emerging specialized platforms continuously innovating to meet evolving market demands. Geographic distribution shows a strong concentration in North America and Europe, reflecting the higher digital maturity and adoption rates in these regions. However, Asia-Pacific is expected to witness significant growth in the coming years as businesses in this region increasingly invest in digital marketing strategies. The future of the Enterprise SEO Platforms market appears promising, with continued growth driven by technological advancements and evolving search engine landscapes. The increasing demand for data-driven decision-making in SEO will further propel the adoption of advanced analytical tools. Furthermore, integration with other marketing platforms, such as CRM and marketing automation systems, will become increasingly crucial for seamless workflow and data-driven campaign optimization. This necessitates the development of more integrated and user-friendly platforms, placing further pressure on vendors to innovate and provide comprehensive, value-added services. Despite these positive trends, challenges remain, including the need for greater transparency in SEO reporting and the ongoing evolution of search engine algorithms, requiring constant adaptation and platform updates.

Open-Source Database Software Market size was valued at USD 11250.75 million in 2024 and the revenue is expected to grow at a CAGR of 10.75% from 2025 to 2032

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Dataset

This dataset was created by MarkSmiths

Contents

This dataset provides comprehensive information and guidance on implementing ROI-driven SEO strategies for Colorado businesses. It covers topics such as measuring SEO performance beyond rankings, identifying high-ROI keywords, integrating analytics and CRM data, and optimizing marketing budgets to drive the highest return on investment.

Database Management Software Market size is expected to develop revenue and exponential market growth at a remarkable CAGR during the forecast period from 2025-2032

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

Database Software Market size was valued at USD 15250.75 million in 2024 and the revenue is expected to grow at a CAGR of 8.2% from 2025 to 2032

Detailed dataset covering comprehensive zip code-specific SEO strategies, local geographic targeting techniques, and neighborhood-level optimization approaches for businesses in Colorado Springs, Colorado.

Results from Checkbot API to measure and collect 341 websites compatibility on multiple SEO variables (34 variables). Checkbot API indexes the website's code to find features capable of impacting SEO performance. Each website has been tested with the maximum number of links allowed to be crawled equally to 10.000 per test. In this way, we retrieved data about the overall websites performance including their sub-pages, and not only the main domain names. A scale from 0 (lowest rate) to 100 (highest rate) was adopted for each examined variable. This constitutes a useful managerial indicator of dealing with the quantification of websites performance while avoiding complex measurement systems that are difficult to be adopted by administrators. Websites tested were also categorized by the CMS type used. More information about the variables and the meaning of the results can be found at https://www.checkbot.io/

This composition appears in the O-Se region of phase space. It's relative stability is shown in the O-Se phase diagram (left). The relative stability of all other phases at this composition (and the combination of other stable phases, if no compound at this composition is stable) is shown in the relative stability plot (right)

Dataset Summary

C-SEO Bench is a benchmark designed to evaluate conversational search engine optimization (C-SEO) techniques across two common tasks: product recommendation and question answering. Each task spans multiple domains to assess domain-specific effects and generalization ability of C-SEO methods.

  Supported Tasks and Domains





  Product Recommendation

This task requires an LLM to recommend the top-k products relevant to a user query, using only the… See the full description on the dataset page: https://huggingface.co/datasets/parameterlab/c-seo-bench.

Data obtained from computational DFT calculations on Cubic SeO is provided. Available data include crystal structure, bandgap energy, stability, density of states, and calculation input/output files.

The AI-based SEO tools market is experiencing robust growth, driven by the increasing need for businesses to optimize their online presence and improve search engine rankings. The market, estimated at $2 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 25% from 2025 to 2033, reaching an estimated market value of $8 billion by 2033. This rapid expansion is fueled by several key factors. Firstly, the rising complexity of SEO algorithms necessitates sophisticated tools that can leverage AI's capabilities for keyword research, content optimization, and technical SEO analysis. Secondly, the increasing adoption of AI-powered content creation and automation features within these tools is streamlining workflows and boosting efficiency for SEO professionals. Finally, businesses of all sizes are recognizing the value of data-driven SEO strategies provided by these platforms, improving their return on investment for digital marketing efforts. Key market trends include the integration of advanced natural language processing (NLP) capabilities for enhanced content analysis and semantic understanding, the rise of AI-powered SEO audit tools for identifying and resolving technical issues, and the increasing focus on personalized SEO strategies tailored to specific target audiences. Despite this growth, several restraints are present. The high cost of implementing and maintaining AI-based SEO tools can pose a barrier for small and medium-sized businesses (SMBs). Furthermore, concerns regarding data privacy and security continue to shape the market landscape, requiring developers to prioritize data protection. The ongoing evolution of search engine algorithms demands continuous updates and improvements to the AI tools, posing a challenge for developers to keep pace with the latest innovations. The market is segmented by tool type (keyword research, content optimization, technical SEO, etc.), deployment model (cloud-based, on-premise), enterprise size (SMBs, large enterprises), and geographical region. Leading players such as Surfer SEO, Frase, Clearscope, and others are actively engaged in innovation, driving market growth through competitive offerings and continuous product improvements. The competitive landscape is marked by both established players and new entrants vying for market share.

Statistical analysis proving each search result page is a unique ecosystem with different user behavior patterns

Data obtained from computational DFT calculations on Hexagonal SeO is provided. Available data include crystal structure, bandgap energy, stability, density of states, and calculation input/output files.