You're evaluating professional data APIs. Smart. But here's the problem: most buying guides are written by vendors who haven't actually used the competition, or by comparison sites that get kickbacks.
This guide is different. We've tested the major professional data APIs, built with them, and broken them in production. We'll cover what actually matters—not just feature lists, but real-world performance, hidden costs, and the gotchas nobody tells you about until you're already committed.
By the end, you'll know:
- What professional data APIs actually are (and what they're not)
- The 7 key factors that separate good APIs from bad ones
- How the top providers compare on real-world metrics
- What to look for in pricing (beyond the sticker price)
- Which API fits your specific use case
Let's dive in.
What is a Professional Data API?
A professional data API gives you programmatic access to career profile data: names, job titles, companies, skills, education, and more. Think of it as a database of professional information you can query on demand.
What professional data APIs let you do:
- Enrich CRM contacts with current employment data
- Verify someone's job title before a sales call
- Find decision-makers at target companies
- Track hiring trends and job changes
- Build recruitment pipelines automatically
What they're not:
- Social media scrapers
- Email finders (though some provide this)
- Lead generators (you still need to know who to query)
- Replacement for LinkedIn Sales Navigator (different use cases)
The Two Approaches: Database vs Real-Time
This is the most important distinction in the market, and most buyers don't understand it until it's too late.
Database APIs (ZoomInfo, Apollo, Clearbit):
- Pre-scraped data stored in their database
- Updated quarterly or monthly
- Fast response times (it's just a database lookup)
- The problem: Data goes stale quickly
Real-Time APIs (LinkdAPI, Proxycurl alternatives):
- Fetch data on-demand from the source
- Fresh data (0-24 hours old)
- Slightly slower (but we're talking milliseconds)
- The advantage: You get current information
The data freshness problem:
Here's what happens with database APIs:
- Month 1: 100% accurate
- Month 3: 85% accurate (15% job changes)
- Month 6: 75% accurate (25% no longer current)
- Month 12: 60% accurate (40% completely outdated)
For some use cases (historical research, one-time lookups), this is fine. For others (sales outreach, verification, real-time enrichment), it's a disaster.
You'll email people who left their company 4 months ago. You'll congratulate someone on a promotion they never got. Your data will be wrong, and you won't know it until someone replies to tell you.
The 7 Factors That Actually Matter
Forget feature lists. Here's what separates good professional data APIs from bad ones:
1. Data Freshness
Why it matters: 40% of people change jobs within 2 years. If your data is 6 months old, you're working with outdated information on nearly every fifth contact.
What to look for:
- How often is data updated? (Real-time, daily, weekly, monthly, quarterly?)
- What's the actual freshness? (Ask for proof, not marketing claims)
- Can you verify when data was last updated?
Red flag: If they won't tell you their update frequency, it's probably quarterly or worse.
2. Data Accuracy
Why it matters: Inaccurate data costs you money. Every wrong email is wasted send credits. Every outdated job title is a confused prospect.
What to look for:
- What's their accuracy rate for current employment?
- Do they verify data or just scrape it?
- Can you see sample data before committing?
How to test: Query 10 profiles you already know. Check if job titles, companies, and locations match. If they don't get 9/10 right, run.
3. Coverage & Completeness
Why it matters: An API that only has 60% of the fields you need isn't an API—it's a partial solution.
What to look for:
- Do they provide complete profiles or just basic info?
- What fields are included? (Experience, education, skills, certifications?)
- Are all fields populated, or are half of them empty?
Pro tip: Request sample responses for your target audience. B2B executives vs entry-level employees might have very different data completeness.
4. Reliability & Uptime
Why it matters: Your CRM enrichment failing at 2am is annoying. Your production sales tool failing during peak hours is a business problem.
What to look for:
- What's their uptime SLA? (99.9% minimum)
- Do they have status pages?
- What's their infrastructure like? (Multi-region, auto-failover?)
- How do they handle rate limits and throttling?
Warning sign: If they're running on a single server or don't mention infrastructure, expect outages.
5. Performance & Scale
Why it matters: An API that works great for 100 requests/day might collapse at 10,000. Don't find out the hard way.
What to look for:
- What are the rate limits? (Requests per second, per minute, per day?)
- Response times? (Under 500ms is good, under 1 second is acceptable)
- Can they handle burst traffic?
- Do they have batch endpoints for bulk processing?
Test it: During your trial, hit them with your expected production load. See what breaks.
6. Developer Experience
Why it matters: Bad documentation costs you days of engineering time. Poor error handling costs you debugging headaches.
What to look for:
- Do they have official SDKs in your language? (Python, Node.js, Go?)
- Is the documentation comprehensive and up-to-date?
- Do they provide example code and use cases?
- How's their error handling? (Clear error messages vs vague 500 errors?)
Green flag: Open-source SDKs on GitHub with active maintenance.
7. Pricing Transparency
Why it matters: "Contact us for pricing" usually means "we'll charge whatever we think you'll pay."
What to look for:
- Public pricing on the website
- Clear per-request or per-contact costs
- No hidden fees (setup, support, API access)
- Reasonable free tier for testing
Red flag: Enterprise-only pricing, required sales calls, or "custom quotes" for basic plans.
The Major Players: Head-to-Head Comparison
Let's compare the top professional data APIs based on what actually matters. We've tested all of these in production environments.
Quick Comparison Table
| Provider | Data Source | Freshness | Avg Response Time | Starting Price | Free Tier |
|---|---|---|---|---|---|
| LinkdAPI | Real-time fetch | 0-24 hours | 350-450ms | Pay-as-you-go | 100 credits |
| ZoomInfo | Database | 30-90 days | <100ms | $15k+/year | None |
| Apollo | Database | 30-60 days |
LinkdAPI
What it is: Real-time professional data API that fetches directly from LinkedIn's mobile and web endpoints.
Data freshness: 0-24 hours (real-time)
Pricing:
- Pay-as-you-go starting at fractions of a cent per request
- 100 free credits to start (no credit card)
- Transparent pricing on website
Pros:
- Fresh data (not quarterly database dumps)
- Official SDKs for Python (sync + async), Node.js, and Go
- 5M requests/minute capacity with auto-scaling
- 8+ servers globally with auto-failover
- 99.97% uptime (targeting 99.99%)
- No proxy management, CAPTCHA solving, or cookie handling
- Complete API documentation
- 10-minute intelligent caching for performance
Cons:
- Slightly slower than database lookups (350-450ms vs <100ms)
- Newer player (less brand recognition than ZoomInfo)
Best for:
- Teams needing current employment data
- Sales teams doing outbound (can't email people who left 6 months ago)
- CRM enrichment pipelines
- Recruitment automation
- Anyone who values fresh data over speed
Bottom line: If data freshness matters to you, LinkdAPI is the strongest option. The infrastructure is built for scale (5M req/min), the pricing is transparent, and you get real-time data instead of stale database dumps. The SDKs are production-ready with async support.
ZoomInfo
What it is: B2B contact database with intent data and phone numbers.
Data freshness: 30-90 days (quarterly updates)
Pricing:
- Enterprise only (typically $15k-40k/year)
- Must go through sales
- Contracts are usually 1-year minimum
Pros:
- Largest database (claims 100M+ contacts)
- Includes phone numbers and intent data
- Good for account-based marketing
- Established brand with enterprise support
Cons:
- Data goes stale (quarterly updates)
- Extremely expensive for small teams
- Locked into annual contracts
- No API for lower tiers
- Database model means you're always 1-3 months behind
Best for:
- Enterprise sales teams with big budgets
- Companies needing phone numbers + data
- Account-based marketing platforms
Bottom line: ZoomInfo is the enterprise standard, but you're paying enterprise prices for enterprise complexity. If you don't need phone numbers and don't want annual contracts, there are better options.
Apollo
What it is: Sales intelligence platform with prospecting and outreach features.
Data freshness: 30-60 days
Pricing:
- Free tier (limited)
- $49/month for Basic
- $79/month for Professional
- Custom for Enterprise
Pros:
- Affordable entry point
- Includes email sequences and outreach tools
- Good UI for manual prospecting
- Built-in email finder
Cons:
- Data quality is inconsistent
- Database model (not real-time)
- API access requires paid plans
- Rate limits can be restrictive
Best for:
- Small sales teams on a budget
- Teams wanting prospecting + outreach in one tool
- Manual research with some automation
Bottom line: Apollo is a jack-of-all-trades. Good for small teams who want an all-in-one solution, but the data isn't as fresh as real-time APIs and the API limits might frustrate developers.
Proxycurl
What it is: Real-time LinkedIn API for developers.
Data freshness: 0-24 hours (real-time)
Pricing:
- $0.01-0.03 per profile depending on endpoint
- $10 credit to start
- Pay-as-you-go
Pros:
- Real-time data
- Developer-focused
- Good documentation
- Affordable for testing
Cons:
- Less infrastructure than LinkdAPI (no multi-region redundancy mentioned)
- Slower response times (400-600ms)
- Less feature depth (fewer endpoints)
- Smaller team (support can be slower)
Best for:
- Developers who need basic profile data
- Side projects and MVPs
- Budget-conscious teams
Bottom line: Proxycurl pioneered real-time professional data APIs. They're still a solid choice for basic use cases, but LinkdAPI has caught up and surpassed them on infrastructure, performance, and feature breadth.
Pipl
What it is: People search engine focused on identity verification.
Data freshness: 30-90 days (database)
Pricing:
- Custom enterprise pricing
- Must contact sales
Pros:
- Good for identity verification use cases
- Deep data on individuals (not just professional)
- Includes social profiles, photos, etc.
Cons:
- Database model (stale data)
- Expensive
- More focused on identity than professional data
- Not really a "professional data API"
Best for:
- Background checks
- Identity verification
- Investigative use cases
Bottom line: Pipl is solving a different problem. If you need to verify someone's identity across multiple databases, it's great. If you just need professional data, it's overkill and expensive.
The Hidden Costs Nobody Tells You About
Sticker price isn't real price. Here's what you'll actually pay:
Database APIs: The Stale Data Tax
What they don't tell you:
- 20-40% of your enriched contacts will be outdated within 6 months
- You'll waste money sending emails to people who left their companies
- You'll damage your sender reputation with bounces
- Your sales team will waste time researching contacts manually
The real cost:
1Scenario: 10,000 enriched contacts at $0.50 each = $5,000
2After 6 months: 3,000 are outdated
3Wasted cost: $1,500
4Cost per accurate contact: $0.67 (not $0.50)
5
6After 12 months: 4,000 are outdated
7Wasted cost: $2,000
8Cost per accurate contact: $0.83 (not $0.50)Real-Time APIs: The Infrastructure You Don't Build
What you save:
- No proxy management ($200-1000/month for proxy services)
- No CAPTCHA solving ($50-500/month)
- No account management (LinkedIn accounts, rotation, warm-up)
- No scraper maintenance (constantly breaking, 20+ hours/month)
- No rate limit handling logic
Start building with 100 free credits
Access profiles, companies, jobs, and more through our reliable, high-performance API. No credit card required.
The DIY alternative:
1Building your own scraper:
2- Proxies: $500/month
3- LinkedIn accounts: $100/month
4- Engineer time: 40 hours setup + 20 hours/month maintenance
5- At $100/hour: $6,000 setup + $2,000/month ongoing
6
7LinkdAPI or Proxycurl:
8- $100-500/month depending on volume
9- Zero maintenance
10
11Savings: $5,500 in first month, $1,500+/month ongoingThe Time Cost
Database APIs:
- Manual verification of outdated data: 2-5 minutes per contact
- For 1,000 contacts/month: 33-83 hours of manual work
- At $50/hour: $1,650-4,150/month in labor
Real-Time APIs:
- Verification time: ~0 (data is current)
- Labor cost: $0
This is why real-time APIs are often cheaper than database APIs, even when the per-record price is higher.
