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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

Apify logo
Apify
✓ verifiedFreemium

Full-stack platform for web scraping, data extraction, and automation; category leader.

4.4M visits/mo2.0K saves
Code Autopilot logo
Code Autopilot
✓ verifiedFreemium

AI GitHub companion that summarizes PRs, answers questions and proposes fixes inside issues and pull requests.

2.6K visits/mo
Gemini Code Assist logo
Gemini Code Assist
✓ verifiedFreemium

Google's AI coding assistant for code completion, generation, chat and review across IDEs and GitHub.

559K visits/mo
Sherloq logo
Sherloq
✓ verifiedFreemium

AI chat assistant for analysts that generates and fixes SQL using an organization's own saved query history.

12K visits/mo
Pricing
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

No public pricing

No public pricing

No public pricing

Core features
  • Web scraping
  • Data extraction
  • Browser automation
  • AI agents
  • Anti-blocking
  • Proxy rotation
  • Open-source tools (Crawlee)
  • Ready-made tools and code templates
  • Chat inside GitHub issues and PRs
  • Task-to-implementation plans with code
  • Automatic bug-fix suggestions
  • Pull-request summaries for faster review
  • Full-codebase context
  • GitHub-native integration
  • Natural language to SQL conversion
  • AI code completion and suggestions
  • Natural-language code generation
  • In-IDE chat assistance
  • AI code review
  • IDE integrations (VS Code, JetBrains, etc.)
  • GitHub integration
  • AI chat trained on the user's own SQL repository
  • query saving, tagging, and versioning
  • team folder permissions and sharing
  • Chrome extension and IntelliJ plugin
  • SOC2-compliant security with no database access needed
  • table and field lookup assistance
Use cases
  • Data for generative AI
  • Lead generation
  • Market research
  • Sentiment analysis
  • Speeding up pull-request reviews
  • Implementing features from task descriptions
  • Debugging with AI-proposed solutions
  • Answering questions about a repo
  • Boosting a solo developer's output
  • Generating SQL queries from text descriptions.
  • Speeding up coding with AI completions
  • Generating code from plain-language prompts
  • Getting in-editor help and explanations
  • Reviewing pull requests with AI
  • Understanding unfamiliar codebases
  • sharing reusable SQL snippets across an analytics team
  • quickly fixing syntax errors in existing queries
  • onboarding new analysts to a team's existing SQL logic
  • building a searchable personal or team SQL knowledge base
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