Compare tools
Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
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Apify
✓ verifiedFreemium
Full-stack platform for web scraping, data extraction, and automation; category leader.
👁 4.4M/mo♥ 2.0K
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EverSQL
✓ verifiedPaid
AI SQL optimizer for PostgreSQL and MySQL; well-regarded niche developer tool.
👁 6.5K/mo
Pricing
Unlocker API: Starts from $1.05/1k req
Crawl API: Starts from $1.05/1k req
SERP API: Starts from $1.05/1k req
Browser API: Starts from $5.88/GB
Scrapers: Starts from $300/mo
Datasets: Starts from $250/mo
Functions: Starts from $2.7/1k req
RetailInsights: Starts from $1,000/mo
Residential Proxies: Starts from $3.53/GB
Datacenter Proxies: Starts from $0.9/IP
ISP Proxies: Starts from $1.3/IP
Mobile Proxies: Starts from $5.88/GB
Custom Scraper: Starts from $300/mo
Free: $0/mo ($5 included usage)
Starter: $29/mo ($26/mo billed annually)
Scale: $199/mo ($179/mo billed annually)
Business: $999/mo ($899/mo billed annually)
Free trial available
No public pricing
Free: $0 /month
Starter: $129 /month
Plus: $490 /month
Enterprise: $2898 /month
Core features
- ✦Multi-engine support (Google, Duckduckgo, Bing, Yandex, Baidu)
- ✦Real-time structured SERP data
- ✦Pay-per-successful-request pricing
- ✦Full JavaScript support
- ✦Precise geo-location targeting
- ✦Structured data delivery in JSON or HTML
- ✦Web scraping
- ✦Data extraction
- ✦Browser automation
- ✦AI agents
- ✦Anti-blocking
- ✦Proxy rotation
- ✦Open-source tools (Crawlee)
- ✦Ready-made tools and code templates
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦Automatic SQL Query Optimization
- ✦Ongoing AI-based Performance Insights
- ✦Cost Reduction Recommendations
Use cases
- →Organic keyword tracking
- →Brand protection
- →Price comparison
- →Market research
- →Detect copyright infringements
- →Ad intelligence
- →Data for generative AI
- →Lead generation
- →Market research
- →Sentiment analysis
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Optimizing slow SQL queries to improve application performance.
- →Monitoring database performance to identify potential bottlenecks.
- →Reducing database costs by identifying redundant indexes and schema optimizations.
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