A Deep Dive into DataForSEO Databases: Key Differences from APIs and Practical Use Cases
Whether you’re running a growing marketing startup or developing enterprise-grade digital marketing solutions, access to quality data remains a cornerstone of success. However, pre-made, one-size-fits-all data sources have become obsolete in the rapidly evolving digital marketing world. So, what solutions can truly meet the data needs of thriving businesses?
In this case, two powerful options stand out — APIs and databases. APIs, or Application Programming Interfaces, deliver data on a request-response model, allowing users to retrieve real-time, tailored data based on specific queries. By fetching data directly from the source, APIs provide up-to-date information within seconds, making them ideal for dynamic applications and automations.
Another option is to use databases as an alternative data source for SEO and marketing. Databases consist of extensive, precompiled datasets that can be delivered directly to the user’s storage. The key benefit of using databases instead of an API-driven approach is instant access to massive amounts of data. Using the specific algorithms, you can immediately fetch data records from the database or run an analysis. While databases don’t provide real-time data, they can be periodically updated to ensure you work with relevant insights. Overall, databases are a comprehensive resource for in-depth, large-scale analysis and historical data access.
Both APIs and databases are powerful data solutions, each with distinct characteristics suited to different needs. But which one — APIs or databases — is the best fit for your project?
In this article, we’ll explore the key factors to consider when choosing between DataForSEO APIs and databases and showcase the capabilities of databases through practical use cases.
Contents:
APIs or Databases: How to choose the right data solution
➤ When to choose DataForSEO APIs over databases
➤ When you should consider DataForSEO databases over APIs
Empowering your solutions with DataForSEO databases: 3 Use cases
➤ Building advanced SEO tools
➤ Comprehensive market research
➤ Training AI and ML models
Conclusion
APIs or Databases: How to choose the right data solution
At DataForSEO, we understand that the data needs of marketers, SEO tool developers, and digital businesses are as varied as the digital industry itself. That’s why we provide access to high-quality data through both APIs and databases, giving our customers flexibility and scalability. Nevertheless, choosing between APIs and databases for your project requires careful consideration of key factors. By evaluating these factors, you can make an informed decision and identify the data solution that best fits your use case.
Let’s explore the factors determining whether APIs or databases are the better choice.
1 When to choose DataForSEO APIs over databases
➤ You require real-time data. If your project requires the most up-to-date data or you need to analyze SERP changes in real-time, APIs are the best option for you. APIs provide immediate updates compared to databases, which contain primarily historical data, such as past SERP rankings or keyword metrics. That’s because APIs retrieve data directly from sources like Google Search, Google Ads, Bing, and Yahoo on a request-response basis. That means you will always get the most accurate and recent insights and can quickly refresh data by sending consecutive API requests.
Moreover, most DataForSEO APIs support two API request methods: Standard and Live. The Standard method works by making separate POST and GET requests for endpoints. On the other hand, the Live method doesn’t require separate requests — it fetches data in real-time. For systems that need to deliver instant results, the Live method is undisputedly the optimal choice.
➤ You’re building a tool that heavily relies on live data. APIs meet the needs of marketing tool developers who want to create new products based on live data or add real-time features to existing solutions. For instance, you can use APIs to develop a keyword research tool for advertisers, utilizing data from Google Ads to display actual CPC, competition, and bid values. Additionally, APIs can help integrate live data features into tools, such as a lead magnet feature offering instant keyword metrics analysis or a website ranking overview.
➤ You need to conduct small or medium-scale research. APIs are especially useful if you run typical SEO analysis or marketing research and need quality data in moderate amounts. For example, you can use APIs to fetch keyword ideas, analyze SERP positions, or retrieve backlink data for a specific website. Besides, you can customize API requests using different parameters to get the correct data without unnecessary bulk. Needless to say, APIs are easy to understand and use even for individual specialists – check out our kickstart guide where we prove it.
➤ You need seamless integration with automation or no-code tools. If you’re looking for solutions to automate manual tasks, such as keyword research or domain analysis, APIs are the perfect choice. You can easily integrate APIs into no-code platforms like Make, Airtable, and Zapier, to build custom workflows and low-level automations with ease. With the robust API data and various integration options, the possibilities for creating tailored solutions are virtually limitless. We showcase some of the automations you can create with APIs in a dedicated blog post.
➤ Your project has a limited budget. APIs are the smart option for companies running cost-sensitive projects. With DataForSEO APIs, you can track your spending and scale your data usage according to your budget. Moreover, unlike many traditional tools, we offer a flexible pay-as-you-go system. You only pay for the data you retrieve, avoiding unnecessary subscription fees or unused features. You can always calculate the cost of API usage by checking our Pricing page.
As you can see, APIs are the optimal choice for projects that require the most recent or real-time insights with no need for extensive storage to support large-scale datasets.
| Choose APIs when: |
|---|
| You need actual, real-time data |
| Building a tool with live data features |
| Conducting small- and medium-scale research |
| You want to create automations, no-code solutions |
| You have a limited budget |
Despite their effectiveness, APIs are not universally suitable for every use case. Although APIs can retrieve data quickly, they are not designed to deliver large volumes of data instantly, and creating extensive datasets using APIs can become prohibitively expensive. In such cases, ready-made databases are a more practical choice. Additionally, databases can surpass APIs as data sources in many other scenarios. Let’s explore the key considerations for choosing databases over APIs.
2 When you should consider DataForSEO databases over APIs
➤ You need immediate access to extensive and structured data. If you require a large volume of data quickly and its freshness is not critical, a database is a wise choice. Creating an extensive dataset using APIs can be time-consuming and resource-intensive, which might not align with your project’s timeline or budget constraints. Purchasing a ready-made database instead saves time and effort, as the data is already ready for immediate use. Moreover, in DataForSEO, we offer regular database updates with a 50% discount, ensuring that the data is still relevant without breaking your budget. For more details, see the Pricing page.
➤ You create sophisticated SEO software that needs historical data. Developing a complex SEO tool with various advanced features can require a lot of historical data. Let’s say you aim to create an advanced rank-tracking tool that can instantly show the customer the ranking dynamics over past time. To do that, you need to analyze loads of historical SERP and ranking data, which is hard to collect on your own. This is entirely achievable with historical SERP databases. By fetching data from such a database, the tool will instantly present a clear picture of a customer’s website ranking trends.
➤ You conduct large-scale market research. Databases can be a lifeline when it comes to extensive, data-driven research. For instance, if you need to analyze a target market with thousands of business entities, gathering data on them through APIs can become prohibitively expensive. Instead, you can simply purchase a comprehensive Business Listings database, giving you immediate access to detailed information on numerous businesses in one place. This can not only save you from unnecessary spending but also significantly accelerate the research process.
➤ Your company has restrictions on the use of third-party integrations. If your organization operates under strict data security policies that limit or prohibit the use of external integrations, databases are the ideal solution. Databases eliminate the need for ongoing third-party connections and ensure compliance with internal security protocols. With DataForSEO databases, you can have full control over your data environment and access extensive datasets without compromising your company’s security requirements.
➤ You need quality datasets for AI development. Access to big volumes of high-quality data is crucial for training effective machine learning and natural language processing algorithms. With proprietary databases, you can quickly obtain SERP and keyword data in enough amounts for extensive AI training. Databases can form the foundation for developing advanced tools like predictive analytics systems, automated content generation, and AI SEO solutions.
Overall, proprietary databases are ideal for those who need instant access to large volumes of structured data. With databases, you can power projects requiring extensive or historical datasets, such as advanced SEO software, large-scale market research, and AI training.
| Choose databases when: |
|---|
| You need a lot of data as soon as possible |
| Building complex tools with historical data |
| Conducting large-scale research |
| You need datasets for AI training |
| You have strict data security policies |
Nevertheless, to fully understand the capabilities of DataForSEO databases, let’s examine some practical cases. For these use cases, our databases are indisputably the best data solution that can ensure project success.
Empowering your solutions with DataForSEO databases: 3 Use cases
1 Building advanced SEO tools
At this point it should be obvious that databases are a perfect match for SEO tool developers who want to create top-notch solutions with various advanced functions. Using databases, you can create complex SEO dashboards with all the essential details and access to historical data.
➤ Rank tracking dashboard
For example, with DataForSEO databases, you can create an average rankings dashboard for a rank-tracking app. While such a dashboard can also be built using APIs, databases offer instant access to far more extensive data records. Additionally, if you opt for a ready-made database, your system won’t need to make repeated API calls. You can also implement your own algorithms to fetch and interpret the data in your preferred format.
As you can see, this dashboard represents the website’s average position over the indicated period. It also has a historical average ranking changes graph to see the fluctuations of the rankings over the year and data on rankings in target locations.
For example, the Average Position graph that displays a website’s average position within a selected time period can be built using both the Google SERP database and the Historical Google SERP database. You can get the current website position for the dashboard with the data from the Regular Google SERP database. This database is based on standard organic, paid results and featured snippets from Google SERPs.
To get the data for previous website positions for this graph, you can use data from the Historical Google SERP database. In this database, the information about the past rankings is located in the serp_info_history objects and available for up to one year.
With data from the same historical database, you can create the Historical Average Ranking Changes graph. You just need to integrate the data for past rankings for each month displayed in the graph. Using this graph, website owners can instantly see the ranking dynamics over the past months.
To show rankings in the target locations, you can retrieve location-specific SERP data snapshots both from the Google SERP and Historical Google SERP databases. For example, you can run algorithms to fetch SERP rankings for Canada, the United States, and the United Kingdom separately and display them in respective parts of the graph.
➤ Backlink profile overview dashboard
The other notable example where you can power your SEO tool with databases is creating a backlink profile overview dashboard like the one below.
This dashboard showcases a complete overview of a website’s backlink profile. It has the following features that can be enabled with data from DataForSEO databases:
- Reffering pages & backlinks over time. This graph can be built using the Backlinks Summary database data, encompassing millions of domains with backlink data. You can fetch the number of referring pages and backlinks in the database from the respective
reffering_pagesandbacklinksfields. The Backlinks Summary database is updated regularly, so you will always have the actual data to update the graph. - Domain rank over time. To display changes in domain rank over time, you can fetch current rankings from the
rankfield in the Backlinks Summary database and past rankings for up to one year frommain_domain_rankfields from the Historical Google SERP database. You can learn more about how we calculate website domain rank in this Help Center article. - Referring pages, IPs, and subnets. This list displays the total number of referring pages, IPs, and subnets for a given website. You can get this data from the
reffering_pages,referring_ipsandreffering_subnetsfields of the Backlinks Summary database. - Referring platform types. This list shows the types of platforms where backlinks are located. The data for this list is located in the
referring_links_platform_typesobject of the same database. - Referring semantic locations. Here, the user will see where the referring links are located in the HTML semantic elements. You will find this data in the database’s
reffering_links_semantic_locationsobject.
For such advanced SEO dashboards, databases provide instant access to massive structured data, freeing you from manually scraping the SERPs or analyzing backlinks.
2 Comprehensive market research
When it comes to large-scale research, the quality and quantity of data are among the most significant factors. However, data collection can be challenging when time is limited for research, and you need to deliver comprehensive results on a strict deadline. Collecting all the necessary data with ready-made tools or APIs may require creating advanced storage and spending dozens of hours structuring a dataset with unique business listings.
In this case, why not purchase a database and get all the data almost immediately? For example, if you’re conducting a market analysis for business expansion, you can easily access detailed competitor data across various locations with our Business Listings database.
This database encompasses up-to-date information on millions of points of interest and business listings around the globe. Each record in this database contains details about the business entity that cover almost all important aspects needed for location-based business research.
To understand it better, let’s look at the data snippet from the Business Listings database.
Example of the data structure in JSON:
{
"title": "Lombardo’s Sicilian Pizza",
"description": "At Lombardo’s, we’ve been using the same family recipe and making our pizzas the same way since 1957. We’re old school for a reason: our pizza tastes better! We make our unique sauce fresh every day, and every Lombardo’s pizza crust is hand rolled, fresh to order, made with a bit more yeast and sugar to cook up quickly with a soft, flavorful inside and a crispy crunch on the bottom. Once you’ve tried Lombardo’s Pizza, it’s sure to become your favorite pizza on the Lakeshore – or anywhere else!",
"category": "Pizza delivery",
"category_ids": [
"pizza_delivery_service",
"meal_takeaway"
],
"additional_categories": [
"Takeout Restaurant"
],
"cid": "2412308833485550683",
"feature_id": "0x881bd66f3e7b5351:0x217a3e1a6471745b",
"address": "1697 W Sherman Blvd, Muskegon, MI 49441",
"address_info": {
"borough": "Glenside",
"address": "1697 W Sherman Blvd",
"city": "Muskegon",
"zip": "49441",
"region": "Michigan",
"country_code": "US"
},
"place_id": "ChIJUVN7Pm_WG4gRW3RxZBo-eiE",
"phone": "+1231-755-8111",
"url": "http://lombardosmuskegon.com/",
"domain": "lombardosmuskegon.com",
"logo": "https://lh5.googleusercontent.com/-V0ln3Z6x3GU/AAAAAAAAAAI/AAAAAAAAAAA/uCt8jeorXhE/s44-p-k-no-ns-nd/photo.jpg",
"main_image": "https://lh5.googleusercontent.com/p/AF1QipO78Xt03XigMUOYDj4DfXL7D3XhU-WRrS-ACAk2=w426-h240-k-no",
"total_photos": 50,
"snippet": "1697 W Sherman Blvd, Muskegon, MI 49441",
"latitude": 43.205452799999996,
"longitude": -86.2853444,
"is_claimed": true,
"attributes": {
"available_attributes": {
"service_options": [
"has_takeout"
],
"accessibility": [
"has_wheelchair_accessible_entrance"
]
},
"unavailable_attributes": null
},
"place_topics": {
"price": 22,
"stromboli": 16,
"sub": 10,
"lunch": 19,
"business": 9,
"pie": 6,
"bacon": 5,
"pickle pizza": 4,
"area": 4,
"hands": 5
},
"rating": {
"rating_type": "Max5",
"value": 4.5,
"votes_count": 279,
"rating_max": null
},
"rating_distribution": {
"1": 12,
"2": 9,
"3": 11,
"4": 32,
"5": 215
},
"people_also_search": [
{
"cid": "15475392251705711269",
"feature_id": "0x0:0xd6c3a342c2c05aa5",
"title": "Fazoli's",
"rating": {
"rating_type": "Max5",
"value": 3.6,
"votes_count": 894,
"rating_max": null
}
},
{
"cid": "15037260989464878387",
"feature_id": "0x0:0xd0af1532f7e49d33",
"title": "Domino's Pizza",
"rating": {
"rating_type": "Max5",
"value": 4,
"votes_count": 323,
"rating_max": null
}
},
{
"cid": "9809710928747836826",
"feature_id": "0x0:0x8823181d9948359a",
"title": "Fricano's Muskegon Lake",
"rating": {
"rating_type": "Max5",
"value": 4.3,
"votes_count": 1123,
"rating_max": null
}
},
{
"cid": "12237806704699654346",
"feature_id": "0x0:0xa9d56c5bf78440ca",
"title": "Jet's Pizza",
"rating": {
"rating_type": "Max5",
"value": 3.8,
"votes_count": 239,
"rating_max": null
}
},
{
"cid": "14673718806912129913",
"feature_id": "0x0:0xcba385829bf75b79",
"title": "Pizza Ranch",
"rating": {
"rating_type": "Max5",
"value": 4.2,
"votes_count": 1674,
"rating_max": null
}
}
],
"work_time": {
"work_hours": {
"timetable": {
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},
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]
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"current_status": "close"
}
},
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"friday": [
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},
"local_business_links": [
{
"type": "menu",
"title": "lombardosmuskegon.com",
"url": "https://lombardosmuskegon.com/menu/"
}
],
"contacts": [
{
"type": "Telephone",
"value": "+12317558111",
"source": "google_business"
}
],
"time_update": "2023-02-15T12:50:30",
"check_url": "https://www.google.com/maps?cid=2412308833485550683&hl=en&gl=US",
"price_level": "inexpensive",
"hotel_rating": null
}
In the dataset, you can find general information about the business entity, such as name, description, location data, website URL, and contact info. Additionally, you can review each business entity’s rating, including the rating value, rating distribution, and quantity of votes. One of the most interesting features of the dataset is that you can find related business entities in the people_also_search array that may be your potential competitors.
Using this data, you can quickly explore the businesses in specific locations, what features and services they use to attract people, and how the customers rate the business. Besides, you can identify related companies that may be your new potential competitors.
3 Training AI and ML models
As AI and ML emerge as revolutionary technologies in the digital sphere, it is no wonder that many specialists want to use them to address customers’ requests. However, creating a tailored AI solution is a complex process requiring relevant data to train the model, and the data collection process may last for a while. With access to DataForSEO databases, you can instantly access vast quality datasets and train your AI and ML solutions much faster.
For example, if you are developing a machine learning model for a keyword research algorithm, you will need enormous keyword datasets to train it properly. For this purpose, you can leverage the DataForSEO Google Keyword database. This database is the biggest commercially available source of SEO keywords enriched with accurate, up-to-date metrics. Additionally, you can purchase the Historical Google Keyword database to access keyword data all the way back to 2019. In this way, you can fuel your algorithms with a detailed background of keyword trends.
Example of the data structure in JSON:
{
"keyword": "races day",
"location": 2036,
"language": "en",
"spell": null,
"spell_type": null,
"keyword_info": {
"search_volume": 260,
"cpc": null,
"competition": 0.01,
"competition_level": "LOW",
"low_top_of_page_bid": null,
"high_top_of_page_bid": null,
"time_update": "2023-03-21T20:25:36.3263513Z",
"categories": [
10014,
13605,
13624
],
"history": {
"202203": 210,
"202204": 170,
"202205": 210,
"202206": 170,
"202207": 260,
"202208": 320,
"202209": 320,
"202210": 720,
"202211": 260,
"202212": 260,
"202301": 170,
"202302": 170
}
},
"extra": {
"core_keyword": null,
"detected_language": "en",
"keyword_difficulty": 57
},
"search_intent_info": {
"main_intent": "informational",
"foreign_intent": [
"navigational"
],
"last_updated_time": "2023-03-02T17:23:41.2125531Z"
}
}
As you can see, for each keyword in the database, you will get metrics such as current search volume, CPC, competition index, and bid values. You will also receive monthly search volume values for previous months. Besides, in the categories array, you will find which product and service categories the keyword is related to.
For example, you can use this data to train the machine learning algorithm to identify keyword trends by analyzing past and current keyword data. Additionally, you can enable the algorithm to propose instant “smart keyword suggestions” based on the keyword product categories, the competition level, and the search volume of keywords.
To sum up, DataForSEO databases are a powerful solution for the most ambitious, data-driven projects. With instant access to extensive data, you can develop advanced SEO solutions, conduct enterprise-grade research, and release your tools in days, not weeks.
Conclusion
The choice between APIs and databases strongly depends on your project’s specific data needs. APIs are ideal for retrieving real-time, precise data with the flexibility to refresh or update frequently. They are useful for small to medium-scale research, integration with no-code solutions, and enabling live data features in tools.
Databases, however, are the go-to solution when you need immediate access to large, precompiled datasets. As you can see from the use cases, databases can be a reliable source of quality data for the most ambitious projects. Whether you’re working with historical data, conducting large-scale market research, or training AI models, databases provide the structured, comprehensive information needed to handle complex, data-intensive tasks with ease.
For every project and use case, DataForSEO has a comprehensive and tailored data solution. Whether you need access to powerful API data or massive structured datasets ready for immediate use, we can satisfy any data needs you have. Contact us now and build something great with DataForSEO!
