Comparison of B2B Data Providers

In the world of B2B marketing and sales, quality data about companies and professionals is the key to success. There are several popular providers offering access to such data through APIs. In this article, we will neutrally compare four solutions: Proxycurl, Coresignal, Clearbit, and Horizon Data Wave. We will examine key parameters - price, data volume, data quality, and API - to help you objectively evaluate the pros and cons of each. The review has a slight marketing tone, gently emphasizing the advantages of Horizon Data Wave for interested readers.

Key Comparison Criteria

When choosing a B2B data provider, it's important to evaluate the following aspects:

• Price – pricing model, availability of free options, and flexibility (fixed rates vs. pay-per-request).
• Data Volume – size and coverage of the database: how many people and company profiles are available, from how many sources the data is collected.
• Data Quality – relevance (frequency of updates), accuracy, and depth of information provided (set of fields, availability of additional information).
• API and Integrations – ease of use of the API, available functions (search queries, webhooks, additional features), and ready-made integrations with other tools.

Below is a summary table that clearly compares Proxycurl, Coresignal, Clearbit, and Horizon Data Wave according to the criteria listed:

Let's take a closer look at each provider - their advantages and disadvantages.

Proxycurl

Proxycurl is a specialized provider known as a tool for extracting and enriching data from LinkedIn. Founded in 2018, Proxycurl offers developers convenient access to data about professionals and companies via API. This service essentially serves as a "layer" between your application and the huge array of information from LinkedIn, allowing you to obtain up-to-date profiles, contacts, and even job postings. Below we look at the strengths and weaknesses of Proxycurl.

Advantages:

• Fresh real-time data. Proxycurl emphasizes operational data acquisition: people and company profiles are pulled directly from LinkedIn upon request, ensuring information relevance. Many users note that the data is "live" and regularly updated, which favorably distinguishes Proxycurl from some competitors with more static databases.
• Rich profile information. The service returns very detailed information: in addition to the main LinkedIn fields, profile photos, company logos and other additional fields are available, which are not always present in alternatives. This provides a more complete picture of a contact or company.
• Flexible and transparent payment model. Proxycurl provides a pay-as-you-go approach: you can buy credits and pay only for completed requests. The cost is very competitive – about $0.01–0.10 per request (depending on the type of data). Subscriptions with volume discounts are available, starting from ~$49 per month for small volumes. An important plus – prices are openly published on the website and you don't need to communicate with the sales department to get started. New users are given a free trial limit (10 credits) for testing the API.
• Developer orientation. Proxycurl has a well-documented REST API with multiple endpoints: separate requests for people profiles, companies, name search, reverse email search, etc. There are ready-made libraries and code examples, which simplifies integration. Proxycurl also supports selling the entire dataset (so-called LinkDB) for tasks where offline database access is needed.
• Accessibility for small businesses. Thanks to the low entry threshold (a few dollars for credits), Proxycurl attracts startups and small companies that need data but don't have resources for large annual contracts. You can start with a small budget and scale usage as you grow.

Disadvantages:

• Narrower source coverage. Unlike multi-platform aggregators, Proxycurl focuses mainly on LinkedIn data. This means that the information is rich in terms of professional profiles, but, for example, there is no separate data from job sites, employer reviews, etc., which some competitors offer. Proxycurl's database volume (about 472 million profiles) is inferior to the largest suppliers focused on large source mergers.
• Legal aspects and limitations. Since Proxycurl essentially parses LinkedIn (bypassing the official LinkedIn API), questions may arise regarding compliance with the platform's terms of use. Proxycurl claims to comply with GDPR/CCPA, but integration should take into account that the data is obtained from public profiles. Companies strictly following platform rules may need to clarify the nuances of using such data.
• Credit system can be complicated. Although the pricing model is transparent, Proxycurl's API requests themselves have different "prices" in credits. For example, getting a full profile can cost several credits (1 to 10) depending on the volume of data returned. Additional parameters (for example, getting email contacts) can also increase the "cost" of the request. Beginners need to carefully study the documentation on credit spending to accurately forecast their budget.
• Annual plans for discounts. For regular use of large volumes, Proxycurl offers subscriptions, but many of them are calculated for an annual contract with monthly payments. Cancellation before the deadline may be accompanied by penalties. That is, despite the ability to pay monthly, you are actually committing for a year. For some clients, this may be inconvenient, although there remains the alternative of simply buying credits as needed without a subscription.

Conclusion on Proxycurl:

This provider is great for developers and small teams who need up-to-date LinkedIn data on demand. Proxycurl stands out for its affordable price and depth of profile data. If your focus is specifically on profiles of professionals and companies from LinkedIn, and you value the freshness of information and the simplicity of the API, Proxycurl is a strong candidate. However, for very large volumes of data or wider coverage of sources (for example, reviews, job postings), additional solutions may be required. Enterprises should also consider the features of the credit model and make sure that such an approach suits them. Overall, Proxycurl is a reliable and flexible B2B data enrichment tool, especially attractive for those looking for a combination of LinkedIn data quality and reasonable price.

Coresignal

Coresignal is one of the biggest players in the B2B data market, offering large-scale aggregated datasets. The company specializes in collecting information from multiple public web sources: LinkedIn (professional profiles), Indeed, Wellfound (AngelList), Glassdoor, GitHub, and other resources. Through this, Coresignal forms an extensive database that includes not only profiles of professionals and companies, but also related data: job postings, staff change histories, company reviews, and more. Let's look at the pros and cons of Coresignal.

Advantages:

• Extraordinarily large volume of data. Coresignal offers truly impressive coverage: according to the stated data, their database contains over 731 million professional profiles and 110 million companies – one of the largest indicators in the market. In addition, the service provides access to almost 500 million job posting records and other types of data. For companies that need mass analysis of the labor market or global coverage of B2B contacts, Coresignal can meet volume needs better than anyone.
• Multi-source and data diversity. Unlike narrowly focused providers, Coresignal combines data from different platforms. For example, employee profiles can be enriched with information from LinkedIn and other sites, company data is supplemented with indicators from various resources (for example, reviews from Glassdoor, vacancies from Indeed, etc.). This approach provides a more complete dossier: you can get a 360° view of a company (profile, employee composition, open vacancies, reviews) or a specialist (profile, resume, activities).
• Consistency and structure. Despite the many sources, Coresignal strives to bring the data to a unified format. As a result, clients receive standardized fields regardless of the original source. For example, JSON responses to API requests have a consistent structure. Coresignal also offers data exports in CSV and Parquet formats for large arrays, which is convenient for analysis. This level of structuring simplifies data integration into the customer's systems.
• Regular updates (data freshness). Coresignal positions its service as a "stream of fresh data about companies and professionals". It is known that data from major platforms is updated very frequently – according to some information, LinkedIn profiles are updated every 6 hours throughout the day. This means that although Coresignal does not provide "real-time" on demand, their data is as close as possible to current, given the scale of the database. For most cases (daily CRM enrichment, weekly analytical exports), this is more than enough.
• Extended API capabilities. For working through the API, Coresignal offers several specialized endpoints: separately for companies, for employees, for job postings, historical data (for example, the API for changes in company size). In addition, there are possibilities for keyword search queries, filtering, and even Elasticsearch integration for complex database searches. An important function is webhooks for data changes: you can receive notifications if, for example, a tracked company's profile has changed or a new job posting has appeared. These features provide more flexibility in creating custom solutions on top of the API.
• Support and service for enterprises. Coresignal is focused on large clients, so it provides personalized support, help in selecting data, the possibility of individual agreements (for example, custom exports, dedicated account managers). For companies with special requirements (separate sources, private deployments), such an approach can be a significant plus.

Disadvantages:

• High entry threshold and cost. Like many enterprise solutions, Coresignal does not publicly disclose detailed prices for large volumes – potential clients are invited to contact the sales department. According to available data, basic access costs are not cheap: acquiring a full data set starts from ~$1000, and API subscriptions from ~$49/month for the minimum package and further depending on the scale. For full use of all the power (hundreds of millions of records), budgets will obviously be measured in tens of thousands of dollars per year. This makes Coresignal unjustifiably expensive for startups and small businesses that need only selective information.
• Complexity of redundant data. The abundance of sources is a double-edged sword. On the one hand, you get a lot of different information, on the other – there may be duplicates or inconsistencies between sources. Coresignal tries to mitigate this with unification, but integrating such a multifaceted database may require more effort in cleaning and matching data. Also, not all business tasks need, for example, data on job postings or reviews – sometimes extra fields only complicate the process. Small teams may find it difficult to extract benefits from all the richness paid for in Coresignal without having data scientists and engineers.
• Orientation towards long-term cooperation. Coresignal is more suitable for cases when a company plans to regularly consume large volumes of web data and integrate them into its processes. If you need a one-time collection or irregular requests, interaction through the sales department and large minimum deals looks cumbersome. There is no familiar self-service model with instant registration and instant access to the API – even starting a free trial will require communication. This reduces attractiveness for those who need "here and now a little data".
• Less responsiveness compared to live APIs. Although data is updated frequently, Coresignal does not provide the ability to request very fresh information on-demand, as Proxycurl does, for example. That is, if at this moment a LinkedIn user has changed jobs, this will be reflected in Coresignal with some delay (a few hours or a day). For most scenarios this is not critical, but for those where instant relevance is required (say, an application that responds to profile changes in real time) – Coresignal may not be suitable.
• Cost of "extra" data. If your company needs only data of one category (for example, only company profiles), you may still have to pay for a large package that includes other categories that you don't use. Individually allocating and paying strictly for the needed fields or sources can be difficult – the package offer covers almost everything. In this sense, you may be paying for data that you do not plan to use.

Conclusion on Coresignal:

This platform is ideal for organizations that need the widest possible coverage of B2B data and are ready to invest in obtaining and processing it. Coresignal provides a whole ocean of information – from basic profiles to job postings and reviews – which opens up huge opportunities for analytics, machine learning, HR-tech, fintech products, etc. If you have a large company or an enterprise-level project requiring integration of huge arrays and support guarantees, Coresignal can become a reliable partner. However, for more modest tasks, the solution looks heavyweight and expensive. In cases where the budget is limited or a quick result is needed without complex integrations, alternatives like Proxycurl or Horizon Data Wave will seem more practical. Coresignal remains the choice for those who really need data on an industrial scale and who are ready to build infrastructure for it.

Clearbit

Clearbit is perhaps one of the most famous brands in the field of data enrichment for sales and marketing. Founded in 2014, Clearbit has made a name for itself as a provider of quality information about companies and contacts that is easy to integrate into business processes. Unlike Proxycurl and Coresignal, Clearbit does not position itself as just a "database" – rather, it is a platform for sales and marketing that enriches your existing customer data. Clearbit is often chosen for integration with CRM, email marketing systems, lead capture forms on websites, etc. Let's consider the advantages and disadvantages of Clearbit.

Advantages:

• High quality and data validation. Clearbit prides itself on the accuracy of its information. According to open data, their own dataset contains information about ~44 million companies and 350 million contacts, with more than 100 different attributes available for each company (from industry and number of employees to technologies used and investments). Clearbit's data sources are more than 250 different points (both public and partner). They combine and verify this data, removing noise and outdated records. As a result, clients receive the most reliable information: current job titles, working email addresses, real phones, etc. Thanks to strict verification, the probability of encountering an incorrect email or "junk" profile is minimal.
• Focus on marketing and sales needs. Unlike the technical API focuses of Proxycurl or the huge raw data of Coresignal, Clearbit was initially created for go-to-market teams. This is manifested in well-thought-out products: Clearbit Enrichment automatically supplements lead cards in CRM with missing data (for example, you received an email from a potential client – Clearbit will add their position, company, industry, social networks, etc.). Clearbit Prospector allows you to find the right people in companies according to specified criteria and get their contacts – indispensable for the sales department. Clearbit Reveal identifies which companies visited your website (by IP address) – useful for B2B marketing. All these tools speak of a deep understanding of user needs: Clearbit does not just provide data, but immediately solves an applied problem.
• Ease of integration and use. The platform provides a simple REST API for developers, but many don't even have to write code – Clearbit has ready-made integrations with popular CRMs (Salesforce, HubSpot), with marketing automation systems, with forms on the website. For example, to enrich leads in Salesforce, it is enough to install their package from AppExchange and configure several fields. This lowers the implementation threshold: even teams without strong technical expertise can use Clearbit data through existing tools. In addition, Clearbit offers convenient dashboards where you can set up enrichment rules, upload lists and monitor credit spending.
• Confidentiality and compliance with requirements. Clearbit pays attention to privacy compliance and data laws. They claim to comply with GDPR, that all contacts have explicit opt-in or are publicly available. Also, being a large company, Clearbit is less prone to risks than startups, which can suddenly change policy or experience disruptions. Corporate clients value Clearbit's stability and its reputation in the market.
• Service and support. As an enterprise-level platform, Clearbit provides customer support, training materials, and consultations on the best use of data. Customer Success Managers are available for large accounts, helping to get the most out of Clearbit products. This is important when you pay significant amounts – you get the appropriate level of attention.

Disadvantages:

• Very high cost for small businesses. One of the most mentioned disadvantages of Clearbit is the price. After a recent acquisition by HubSpot and refocusing, Clearbit stopped publishing prices on the website altogether – potential clients are invited to fill out a form and discuss the tariff. From various sources it is known that prices are sometimes unjustifiably high for the volume of data. For example, Clearbit Prospector (contact search) started at around $999 per month, and a full package of tools can cost tens of thousands of dollars per year. For a small company or startup, such amounts are usually excessive, especially when there are alternatives with a smaller price tag. In addition, Clearbit's cost calculation model can be confusing – it depends on the number of contacts in your database, web traffic, number of users, etc., which makes it difficult to forecast the budget.
• Limited free version. Clearbit offers very modest trial possibilities. For example, for the API enrichment, they usually give about 50–100 free requests, which is enough only for basic acquaintance. Full-fledged integration testing practically requires paying for a minimum package. Unlike Proxycurl or Horizon, where you can use it for some time for free or for a small fee at low volumes, with Clearbit you will quickly run into the need to seriously pay to continue. This can discourage individual developers or experimenting teams.
• Less detailed person profiles. Despite the extensive data, Clearbit typically operates with contact information and firmographics, but does not provide a complete profile of a person in the form of, say, LinkedIn. That is, you will get the current position, social networks, work experience (possibly only the last one), but not the entire list of previous jobs, not the entire list of skills or recommendations. For marketing, this is often not needed, but for HR analytics or deep profiling, it may not be enough. In such cases, solutions like Proxycurl/HDW, which pull the entire LinkedIn profile, will be more useful.
• Lack of "actions" and additional types of data. Clearbit does not provide data on job postings, does not give the ability to write to a person or somehow interact – it is strictly a source of data, and only for companies and contacts. If your tasks go beyond enriching contacts (for example, analyzing reviews or automating outreach directly), you will need additional tools. While some competitors are expanding functionality (see Horizon Data Wave with its ability to take actions), Clearbit sticks to its niche.
• Closed ecosystem. Clients note that Clearbit, after being purchased by HubSpot, has become more integrated into the HubSpot ecosystem. For example, a product called Clearbit for HubSpot (so-called Breeze) has appeared, which natively integrates into HubSpot CRM. On the one hand, this is a plus for HubSpot users, on the other – a signal that the company's strategy is shifting towards large platforms. Independent use is possible, but the emphasis may not be on it. Also, any changes in HubSpot's policy can affect the availability of data. In general, dependence on a single vendor is a factor that some businesses try to avoid.

Conclusion on Clearbit:

This provider is ideal for B2B marketing and sales teams that are ready to invest in quality data enrichment and value the simplicity of integration with existing tools. Clearbit provides high accuracy of contact data and a rich company profile, which helps to target advertising, increase lead conversion, personalize communication. If you already have established processes and budget, Clearbit will become a reliable data provider for scaling these processes. However, objectively, the cost and closed nature make it not the best choice for small companies or experimental projects. In cases where a more flexible and affordable approach is needed (especially for developers), it is worth looking at Proxycurl or Horizon Data Wave. Nevertheless, Clearbit maintains a reputation as a premium solution for B2B data enrichment among large clients with an emphasis on marketing.

Horizon Data Wave

Horizon Data Wave (HDW) is a relatively new market participant offering a fresh look at B2B data. If Proxycurl and Coresignal emphasize data, and Clearbit – integration, then Horizon Data Wave tries to combine the best of both worlds. This service provides complete data of LinkedIn profiles and companies via API, and in addition a unique opportunity to automate interactions: you can not only get data, but also perform an action – for example, send a message to a contact or make a request to add to the network directly through the API. HDW positions itself as a platform for data enrichment and for implementing them in your AI applications and bots. Let's consider what makes Horizon Data Wave stand out, and what disadvantages it has.

Advantages:

• Full coverage of LinkedIn data. Horizon claims to aggregate complete information from LinkedIn (and some other platforms) in real time. Practically, this means access to profiles of all LinkedIn users (more than 800–900 million profiles worldwide) and company pages. You get all the key profile information: work experience (all places, positions, dates), education, skills, certificates, recommendations, activities (posts), etc. For companies – description, industry, size, offices, list of employees, company posts and more. In essence, HDW strives to provide a mirror of LinkedIn, but through a convenient API. For many tasks (candidate search, lead generation), this data set is more than enough, and there is no need to involve dozens of sources.
• Real-time data and constant updating. One of the main "features" of Horizon Data Wave is real-time data updates. The system constantly scans sources so that when you request, it provides the most up-to-date information. Thus, you can be sure that you are getting current titles, places of work, fresh posts – all changes on LinkedIn will be reflected immediately. This favorably distinguishes HDW from more traditional providers with periodic updates. Especially for AI applications and bots that should operate with current information (for example, to mention the user's latest post in a personalized message) – relevance is critical.
• Built-in automation of actions (unique feature). HDW's unique difference is the ability to not only read but also act in social networks through the API. The service allows you to connect accounts (for example, your corporate LinkedIn profile) and then perform typical actions through the API: send messages to users, send requests to add contacts, leave comments or post on behalf of the account. This opens up new scenarios: for example, your script can automatically find suitable leads (based on LinkedIn data) and immediately initiate contact with them, bypassing manual work. For sales departments, this is a path to automating routine (a personal bot writing to potential clients), for HR – auto-invitations to candidates, for marketing – automatic audience engagement. None of the competitors considered above provides similar functionality out of the box.
• Simple and transparent pricing. Horizon Data Wave attracts with an extremely understandable payment model: only $0.02 per request. There are no complex tariff plans, no divisions by data types – one price for any API access. At the same time, 100 free requests are given each month, which allows you to start using the service without payment and even permanently cover small needs for free. This approach stands out favorably against the background of competitors with their cumbersome subscriptions and credits. It is especially attractive for small projects and developers: you know exactly how much you will pay, and you pay only when you actually use the service.
• AI orientation and simple integration. HDW promotes itself as a tool for enriching AI agents and applications with data. In practice, this is expressed in convenience for developers: there is detailed documentation, SDK, code examples. It is stated that integration can take just "2 lines of code" – of course, a marketing simplification, but the point is that it is really easy to start. The data is formatted in JSON for popular ML frameworks, which facilitates their feeding to AI models. In general, Horizon Data Wave emphasizes that clients should start getting benefits as quickly as possible – be it a weekend test project or implementation in a large system.
• Flexibility for different scales. On the one hand, the service is accessible and beneficial to small users (thanks to pay-as-you-go and free requests), on the other – it is scalable for enterprise. There is an opportunity to switch to an enterprise plan with a personal approach (for example, if you need integration of custom data sources, increased limits, special support). Thus, Horizon can grow with your project: start for free, then pay pennies per request, and in the long term – establish closer cooperation if necessary, while remaining on a predictable payment model.

Disadvantages:

• Focus primarily on LinkedIn. Like Proxycurl, Horizon Data Wave is essentially oriented towards data from LinkedIn (plus, possibly, some data from other social networks, but they are not emphasized). If you need data outside of LinkedIn – for example, lists of conference participants, information from job sites or internal databases – HDW will not provide this. For most scenarios, LinkedIn profiles are enough, however Coresignal, for example, has a wider coverage of other sources. Here Horizon has consciously occupied the LinkedIn niche, and outside it, capabilities are limited.
• Young product on the market. Since Horizon Data Wave is a new solution, it doesn't yet have such a promoted brand and possibly fewer established integrations. If Proxycurl and Clearbit have been talked about for several years and have reviews, cases, then there is less information about Horizon so far. Someone may find it unusual to trust a less known provider. Nevertheless, the rapidly gaining popularity innovative function (action automation) helps it gain trust from a certain audience.
• Dependence on platform rules. The ability to perform actions through a LinkedIn account is a double-edged sword. On the one hand, it's an innovation, on the other – it implies authorizing your social accounts and potentially can face platform limitations (LinkedIn does not welcome automation of actions very much). Horizon, of course, claims to comply with the rules and have safeguards against exceeding limits, but companies should wisely use this function to avoid violating LinkedIn policies. However, this is not so much a disadvantage as a feature of the application area.
• Lack of ready "boxed" integrations. At the time of review, Horizon Data Wave has fewer ready connectors to CRM or other systems (compared to Clearbit). That is, integration goes through direct use of the API. For developers, this is not a problem at all, but business users without programmers may need the help of an integrator. However, with a simple API, this task can be easily solved with third-party tools (for example, using Zapier/Webhook or a small script).

Conclusion on Horizon Data Wave:

This is a promising solution for those who need fresh LinkedIn data and the ability to instantly use it. Horizon Data Wave is particularly attractive for modern scenarios: integration with AI bots, automation of sales and recruiting, when it is required not only to know about the target client, but also to immediately establish contact with them. Thanks to the transparent price of $0.02 per request and absence of bureaucracy, HDW is available to a wide range of users – from independent developers to large teams. If you are looking for an alternative to old expensive providers, Horizon Data Wave provides a comprehensive solution: data + action. Yes, it falls short in terms of source coverage compared to Coresignal and is less known so far, but the combination of rich LinkedIn information, real-time, and automation makes it a unique offering in the market.

Conclusion

In the market of B2B data providers, there is no universal winner – the choice depends on your tasks and priorities. Proxycurl excels at promptly obtaining LinkedIn profiles on request, attracting with flexible payment and developer orientation. Coresignal provides unprecedented scale and many types of data, which is ideal for companies craving data "in large chunks" and ready to invest resources. Clearbit maintains leadership as a premium solution for marketing and sales, where accuracy, lead enrichment, and built-in integrations are valued, albeit at a high price.

Horizon Data Wave, in turn, has entered the arena, combining the strengths of competitors and bringing innovation. It is simple to start working with, gives fresh and complete LinkedIn data, and plus to this – allows you to immediately act on the basis of this data. Such an approach can save time and open new opportunities (for example, automated outreach), which is especially valuable in the era of AI and business process automation.

If you need a neutral and objective view, then all four providers are worthy of attention, each with its own niche. However, evaluating price, volume, quality, and API functionality, you may notice that Horizon Data Wave stands out favorably with the balance of these parameters. Its transparent pricing and innovative features make it an attractive choice for those looking for a modern and effective solution without overpayments. Ultimately, the best data provider is the one that most fully satisfies the needs of your business. And for many companies seeking to get maximum value from data at a reasonable budget, Horizon Data Wave can become just such a solution, successfully combining rich data, convenience, and innovation.

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