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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.
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OpnForm
✓ verifiedPaid
Open-source AI form builder for free forms and surveys; strong adoption and traffic.
30K visits/mo684 saves
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devActivity
✓ verifiedFreemium
GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
52K visits/mo
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Kaggle
✓ verifiedFree
Google-owned hub for data scientists to find datasets, enter ML competitions, run notebooks, and learn.
Pricing
No public pricing
Free: $0
Pro (Monthly): $16 per month
Pro (Yearly): $16 per month (billed yearly)
Free: $0/contributor (up to 7 contributors, 90-day retention)
Premium: $10/contributor (unlimited contributors, AI insights)
No public pricing
No public pricing
Core features
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- ✦AI Form Builder
- ✦Unlimited forms, fields, and responses (Free plan)
- ✦Form logic, URL pre-fill, Hidden fields
- ✦File uploads, Custom code, Webhooks
- ✦Customizable themes and thank you pages
- ✦Form Analytics
- ✦Contribution and work-quality analytics
- ✦Automated, AI-powered performance reviews
- ✦Retrospective insights
- ✦Operational bottleneck alerts
- ✦Gamification with XP, levels and leaderboards
- ✦Uses Git metadata without accessing source code
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- ✦Public dataset repository
- ✦Machine-learning competitions with prizes
- ✦Browser-based notebooks with free GPU/TPU
- ✦Micro-courses on data science topics
- ✦Community forums and shared code
Use cases
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- →Creating contact forms
- →Conducting surveys
- →Collecting internal announcements
- →Managing warehouse inventory check-ins
- →Gathering training feedback
- →Processing international job applications
- →Streamlining legal petitions
- →Supporting environmental initiatives
- →Automating developer performance reviews
- →Spotting delivery bottlenecks
- →Generating retrospective insights
- →Motivating teams via gamification
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- →Practicing and benchmarking ML models
- →Finding datasets for analysis
- →Competing in predictive-modeling contests
- →Learning data science skills
- →Sharing reproducible notebooks
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