Database Platform Cost Analysis: MongoDB Atlas vs PlanetScale vs Supabase

Executive Summary

Critical Decision Framework:

• Bootstrap/Indie: Supabase only viable option with functional free tier
• Predictable Scaling: PlanetScale expensive but transparent
• Enterprise/VC-Funded: Atlas acceptable if budget allows 2-3x overruns

Budget Reality Check: Expect 2-3x advertised pricing across all platforms due to hidden costs.

Production Cost Comparison

Platform	Entry Production	Mid-Scale Reality	Enterprise
MongoDB Atlas	M10: $57→$150/month Index bloat forces upgrades Peak billing traps	M30: $250→$400/month Auto-scaling disasters Where most users trapped	M60+: $1,000+/month Finally includes support
PlanetScale	PS-10: $39/month base Predictable, no surprises No free tier (killed 2024)	PS-20: $59 + $1.50/GB Storage costs accumulate Still cheaper than Atlas	Enterprise: Contact pricing Expensive but stable
Supabase	Pro+Micro: $35/month Includes auth/realtime/storage Spend caps prevent disasters	Pro+Small: $65/month Real-time billing dashboard ARM instances faster	Team: $599/month Still cheaper than Atlas SOC2 compliance

Critical Failure Modes

MongoDB Atlas Budget Destruction Patterns

Index Bloat Trap:

• Performance Advisor suggests indexes automatically
• 20-40% storage overhead per index recommendation
• 8GB dataset → 12GB overnight from hidden indexes
• Triggers automatic tier upgrades: M10 ($57) → M20 ($115)
• Solution: Ignore 50% of Performance Advisor suggestions

Peak Usage Billing Trap:

• Bills for highest usage during entire month
• 2-hour traffic spike = 30 days of peak pricing
• M10 → M30 upgrade during spike = $250/month permanently
• Solution: Disable auto-scaling, accept degraded performance

Hidden Backup Costs:

• $0.045-0.063/GB/month not included in base pricing
• Discovered only after first bill
• No opt-out option for production clusters

PlanetScale Storage Cost Escalation

Storage Pricing Reality:

• $1.50/GB total cost (3x replication included)
• 100GB database = $150/month storage alone
• Plus base plan costs
• Storage auto-scales without warnings

Supabase Spend Cap Limitations

PITR Backup Pricing:

• Point-in-time recovery: +$100/month
• Essential for production but expensive
• Default backups: 7-14 days only

Resource Requirements

Minimum Production Specs

For 10k Active Users (Typical SaaS):

• Atlas: M20 minimum ($115-150/month) for stable performance
• PlanetScale: PS-10 + storage ($60-80/month) handles load well
• Supabase: Pro + Micro compute ($35-50/month) sufficient

Migration Costs

Time Investment:

• Atlas → Supabase: 2-3 weeks for complex schemas
• Custom migration scripts required for data type mismatches
• Timestamp format incompatibilities common
• Test migration thoroughly before production switch

Operational Expertise Required:

• Atlas: MongoDB query optimization, index management
• PlanetScale: MySQL/Vitess understanding, branch workflow
• Supabase: PostgreSQL knowledge, usage monitoring

Decision Criteria Matrix

Choose Supabase If:

• Bootstrap/indie development budget
• Need auth + realtime + storage included
• Want predictable billing with spend caps
• Require functional free tier for MVP
• Building on PostgreSQL acceptable

Choose PlanetScale If:

• Need zero-downtime schema migrations
• MySQL/Vitess expertise available
• Predictable costs more important than total cost
• Can afford 3x premium for reliability
• Database branching workflow valuable

Choose Atlas If:

• MongoDB required for specific use case
• Enterprise support budget available ($1,000+/month)
• VC funding covers cost overruns
• Team has MongoDB DBA expertise
• Can implement strict index management

Cost Optimization Strategies

Atlas Damage Control

Immediate Actions:

• Disable auto-scaling cluster-wide
• Set billing alerts at 50% (not 90%)
• Review and delete redundant indexes monthly
• Enable Online Archive for data >6 months old ($0.0025/GB vs $0.15/GB)
• Implement connection pooling to prevent forced upgrades

Performance vs Cost Trade-offs:

• Accept 100ms slower queries to avoid index overhead
• Use degraded performance during spikes vs auto-scaling
• Archive old data aggressively to avoid tier upgrades

PlanetScale Optimization

Storage Management:

• Branches share storage until schema divergence
• Data import/export free (unlike Atlas egress charges)
• Storage auto-scales without plan upgrades
• Monitor $1.50/GB accumulation closely

Supabase Cost Control

Scaling Strategies:

• ARM instances faster AND cheaper than x86
• Micro compute handles 10k+ DAU unexpectedly well
• Set spend caps before traffic spikes
• Usage-based billing scales down during low traffic

Critical Warnings

What Documentation Doesn't Tell You

Atlas Hidden Costs:

• Data transfer: Full AWS egress rates (~$0.12/GB)
• Support: Community tier effectively useless
• M0 sandbox: Crashes during load testing/demos
• Connection limits force tier upgrades

PlanetScale Reality:

• Free tier eliminated March 2024 (betrayed indie developers)
• Storage costs can exceed compute costs quickly
• Enterprise features require significant budget

Supabase Gotchas:

• Free tier legitimately works but 500MB limit firm
• PITR backups expensive but essential for production
• Edge Functions scale well but monitoring required

Traffic Spike Disaster Prevention

Set Before Launch:

• Atlas: Disable auto-scaling, set 50% billing alerts
• PlanetScale: Monitor storage growth during traffic
• Supabase: Enable spend caps, monitor ARM compute scaling

Expected Costs During Viral Traffic:

• Atlas data transfer can cost $200-300/day
• PlanetScale handles spikes without surprise charges
• Supabase pauses gracefully at spend cap limits

Breaking Points and Failure Thresholds

Performance Degradation Points

Atlas:

• M0: Unusable under any real load
• M10: Adequate until index bloat triggers upgrade
• Shared CPU crashes during demos consistently

PlanetScale:

• PS-10: Handles production loads well due to Vitess architecture
• 3-node cluster provides actual high availability
• Query insights actually helpful (unlike Atlas Performance Advisor)

Supabase:

• Free tier: 50k MAU limit generous for MVPs
• Micro compute: 10k+ DAU before performance issues
• ARM instances outperform x86 for Node.js workloads

Financial Breaking Points

Budget Destruction Scenarios:

• Atlas index recommendations → 40% cost increase
• Atlas auto-scaling during traffic → permanent tier upgrade
• PlanetScale storage growth → linear cost increase
• All platforms: Data transfer during viral content

Acceptable Loss Thresholds:

• Atlas: Budget 3x calculator estimates
• PlanetScale: Budget 2x for storage growth
• Supabase: Actual costs match calculator with spend caps

Tool Dependencies and Hidden Costs

Required Additional Tools

Atlas Ecosystem:

• MongoDB Compass: Free but crashes frequently
• TablePlus: $89 but reliable
• Premium support: $1,000+/month for human responses

PlanetScale Workflow:

• CLI tools included and stable
• Query insights built-in
• Business support included all plans

Supabase Integration:

• All tooling included in pricing
• Real-time dashboard actually works
• Community support responsive

Development Environment Requirements

Local Development:

• 32GB RAM recommended for MongoDB + Docker + development tools
• 16GB insufficient for full stack with Atlas
• PlanetScale CLI UTF-8 issues on Windows PowerShell
• Atlas Compass M1 Mac compatibility problems

Implementation Success Criteria

Technical Validation

Pre-Production Testing:

• Load test with expected peak traffic + 2x margin
• Test backup/restore procedures completely
• Validate spend cap behavior under load
• Document migration rollback procedures

Operational Readiness:

• Billing alerts configured at 50% thresholds
• Monitoring dashboards for all cost drivers
• Team training on platform-specific optimization
• Customer communication plan for service pauses

Financial Validation

Budget Reality Check:

• 3x advertised pricing for Atlas planning
• 2x base pricing for PlanetScale storage scaling
• Actual costs match Supabase calculator with spend caps
• Data transfer costs during viral content scenarios

Success Metrics:

• Predictable monthly billing (±20%)
• No surprise charges >$100/month
• Performance adequate during 10x traffic spikes
• Support response times <24 hours for production issues