Real-time vs Cached Data: Which is Better? (2026)
Compare real-time and cached data for B2B applications. Performance, cost, accuracy, and use cases for each approach.
Understanding the Difference
When choosing a B2B data enrichment provider, one of the most important decisions is whether to use real-time or cached data. This choice significantly impacts data accuracy, API performance, and costs.
Real-time Data
Real-time data is fetched live from source systems when you make an API request. The provider queries multiple data sources, aggregates the information, and returns current data.
Cached Data
Cached data is pre-collected and stored in a database. When you make an API request, the provider returns data from their cache, which may be weeks or months old.
Detailed Comparison
| Factor | Real-time | Cached |
|---|---|---|
| Data Freshness | Current | 3-6 months old |
| Accuracy | 90-95% | 70-80% |
| Response Time | <2 seconds | <1 second |
| Cost | $49-299/mo | $499-2,999/mo |
| Coverage | Global | Limited |
| Match Rate | 85-90% | 60-70% |
Real-time Data: Pros and Cons
Advantages
- Always Current: Data is fetched live, ensuring accuracy
- Higher Accuracy: 90-95% accuracy vs 70-80% for cached
- Better Coverage: Can access profiles not in cached databases
- Lower Cost: Modern providers like Netrows charge 10x less
- No Stale Data: Never worry about outdated information
- Global Reach: Access data from any country
Disadvantages
- Slightly Slower: 1-2 seconds vs instant for cached
- Rate Limits: Subject to upstream API limits
- Dependency: Relies on source system availability
Best Use Cases
- Sales intelligence and lead enrichment
- Recruitment and talent sourcing
- Real-time CRM updates
- Account-based marketing
- Competitive intelligence
Cached Data: Pros and Cons
Advantages
- Instant Response: Sub-second API response times
- Predictable Performance: No dependency on external systems
- Bulk Operations: Can process millions of records quickly
- Historical Data: May include historical snapshots
Disadvantages
- Outdated Data: Information can be 3-6 months old
- Lower Accuracy: 70-80% accuracy due to stale data
- Limited Coverage: Only profiles in their database
- High Cost: $499-$2,999/month for enterprise plans
- Missing Profiles: New professionals not in cache
- Job Changes: Doesn't reflect recent career moves
Best Use Cases
- Bulk data enrichment (millions of records)
- Historical analysis and trends
- Applications requiring sub-second response
- Offline data processing
Performance Comparison
Response Times
Real-time (Netrows): <2 seconds average
Cached (Clearbit): ~5 seconds average
Cached (ZoomInfo): ~8 seconds average
Surprisingly, real-time providers like Netrows are often faster than cached providers due to modern infrastructure and optimized data fetching.
Throughput
Real-time: 10-100 requests/minute (plan-dependent)
Cached: 600 requests/hour (10/minute)
Real-time providers often offer higher rate limits since they don't need to maintain massive databases.
Reliability
Real-time: 99.9% uptime (Netrows)
Cached: 99.5% uptime (industry average)
Cost Analysis
Real-time Pricing (Netrows)
- Starter: $49/month for 10,000 credits
- Growth: $299/month for 100,000 credits
- Pay-as-you-go: $10-$300 for credit packages
- Cost per enrichment: $0.005-$0.03
Cached Pricing (Traditional Providers)
- Clearbit: $499-$2,999/month
- ZoomInfo: $14,995-$50,000/year
- Cost per enrichment: $0.50-$2.00
š° Cost Savings
Real-time data from Netrows costs 10-100x less than cached data from traditional providers, while providing better accuracy and freshness.
Accuracy Comparison
Why Real-time is More Accurate
Real-time data is more accurate because:
- Current Information: Fetched at request time
- Job Changes: Reflects recent career moves
- Company Updates: Shows current employer
- Profile Changes: Includes latest skills and experience
- No Decay: Data doesn't become stale
Cached Data Accuracy Issues
Cached data becomes less accurate over time:
- Job Changes: 20-30% of professionals change jobs annually
- Company Changes: Mergers, acquisitions, rebrands
- Profile Updates: New skills, certifications, experience
- Contact Info: Email addresses and phone numbers change
- Location Changes: Relocations and remote work
Accuracy Over Time:
Month 0: 95% accurate (freshly cached)
Month 3: 80% accurate
Month 6: 70% accurate
Month 12: 50% accurate
Real-time data maintains 90-95% accuracy regardless of when it's accessed.
Hybrid Approach
Some applications benefit from combining both approaches:
Strategy 1: Cache + Refresh
- Use real-time API for initial enrichment
- Cache results locally for 30-90 days
- Refresh cache periodically with real-time data
- Best for: High-volume applications with budget constraints
Strategy 2: Tiered Enrichment
- Use cached data for bulk screening
- Use real-time data for qualified leads
- Prioritize real-time for high-value prospects
- Best for: Lead qualification pipelines
Strategy 3: Smart Refresh
- Check cache first
- If data is older than 90 days, fetch real-time
- Update cache with fresh data
- Best for: Cost optimization
Decision Framework
Choose Real-time Data If:
- Data accuracy is critical
- You need current job titles and companies
- You're targeting active job seekers
- You want to minimize costs
- You need global coverage
- You're enriching qualified leads
Choose Cached Data If:
- You need to process millions of records
- Sub-second response time is required
- You need historical data analysis
- You're doing offline batch processing
- Data freshness is less important
Choose Hybrid Approach If:
- You have high volume but need accuracy
- You want to optimize costs
- You have tiered lead qualification
- You need both speed and freshness
Real-World Examples
Example 1: SaaS Startup
Challenge: Enrich 5,000 leads/month with limited budget
Solution: Real-time data from Netrows
Result: 95% accuracy at $49/month vs $499 for cached data
Example 2: Recruitment Agency
Challenge: Find candidates with current job titles
Solution: Real-time data for active candidates
Result: 40% higher placement rate due to accurate data
Example 3: Enterprise Sales Team
Challenge: Enrich 100,000 leads/month
Solution: Hybrid approach (cached screening + real-time for qualified)
Result: 80% cost savings while maintaining accuracy for important leads
Frequently Asked Questions
Is real-time data always more expensive?
No. Modern real-time providers like Netrows are actually 10x cheaper than cached data providers. Real-time data costs $49/month vs $499+ for cached data.
How often should I refresh cached data?
Refresh every 30-90 days depending on your use case. Sales teams need fresher data (30 days), while market research can use longer periods (90 days).
Can I build my own cache with real-time data?
Yes. Fetch data from real-time APIs and cache locally. This gives you the best of both worlds: fresh data when needed and fast lookups for cached records.
Why is cached data so expensive?
Traditional providers maintain massive databases and charge premium prices. Real-time providers don't need expensive infrastructure, passing savings to customers.
Which approach is better for GDPR compliance?
Real-time data is often better for GDPR since you're fetching current, publicly available information. Cached databases may contain outdated data that individuals want removed.
Can real-time data handle high volume?
Yes. Netrows supports 10-100 requests/minute (6,000/hour), sufficient for most applications. For higher volume, use caching or contact us for enterprise limits.
What if the real-time API is down?
Implement fallback logic: check cache first, then call real-time API. Real-time providers like Netrows offer 99.9% uptime SLA.
How do I measure data freshness?
Track the "last_updated" timestamp from your provider. Real-time data should have timestamps within minutes. Cached data may show timestamps months old.
Get Real-time Data at Cached Data Prices
Netrows provides real-time B2B data at $49/month - 10x cheaper than cached data providers. Get started with 100 free credits today.