Should I just use PostgreSQL and call it a day?

**Yes.** Stop overthinking this. PostgreSQL is better than MySQL in every way that matters. Better JSON support, window functions, proper full-text search, and a community that isn't owned by Oracle. **When to stay on MySQL:** You have 500+ stored procedures, your entire team would quit if you changed databases, or you're too scared to make the switch. Otherwise, just migrate to PostgreSQL already. I've migrated eight different apps from MySQL to PostgreSQL. The switch was worth it every single time.

Is PlanetScale's $399/month plan worth it?

**Hell no.** Unless you're doing some serious branching gymnastics, you're paying $300 extra for features you don't need. Their connection limits are designed to force upgrades. **When PlanetScale makes sense:** You're deploying schema changes multiple times per day and can't figure out proper staging environments. The branching is genuinely useful, but expensive. **Better option:** Use PostgreSQL with proper staging environments. Save $200+/month and get better database features.

Will MongoDB bankrupt me?

**Probably.** MongoDB Atlas pricing is designed to surprise you. Connection pooling costs, backup storage, network egress - it all adds up fast. We got a $2.2k bill because our Node.js app was leaking connections. **When MongoDB is worth it:** You're storing genuinely document-shaped data (like CMS content) and your queries are simple. For most web apps, you're just making your life harder. **Cost control:** Use connection pooling correctly or your bill will explode. Also, their "serverless" tier has hidden limits that'll bite you.

Can Supabase handle real production traffic?

**For most startups, yes.** It's PostgreSQL with a nice dashboard. But their real-time features break at scale and edge functions timeout randomly on large payloads. **When Supabase works:** MVPs, side projects, and apps with < 10k users. The auth integration is genuinely useful and saves weeks of development. **When to avoid:** Your app gets serious traffic or you need consistent real-time features. Switch to regular PostgreSQL RDS at that point.

Should I trust Neon with my production data?

**If you need serverless PostgreSQL, yes.** Their cold starts suck on the free tier but the paid tier is solid. The branching feature is actually useful (unlike fake database branching). **Cost reality:** The $19 Launch plan gets you started but real usage hits $69+/month fast as you scale up compute and storage, which is still reasonable for serverless PostgreSQL. **Production concerns:** They're newer than AWS RDS but built on proven PostgreSQL. I'd trust them for most applications.

Is CockroachDB overkill for my startup?

**Absolutely.** Unless you're building the next Stripe, you don't need distributed ACID transactions. CockroachDB is slow and expensive for single-region apps. **When CockroachDB makes sense:** Multi-region financial apps that can't lose data. Banking, payments, anything where consistency across continents matters more than latency. **Cost warning:** Starts at $100/month, scales to bankruptcy fast. Only worth it if you're already making money and need the guarantees.

How long will migration actually take?

**PostgreSQL migration:** 3-4 weeks if you're competent. Add another 2 weeks for finding all the edge cases your tests missed. **PlanetScale migration:** 1 week to remove all your foreign keys, 3 months to fix the data integrity issues. **MongoDB migration:** 6+ months of pain. You'll rewrite everything twice because the first version will be garbage. **Aurora MySQL:** 2 days unless you're using weird MySQL features. **Timeline reality:** Everything takes twice as long as you think. Plan accordingly.

What breaks when you actually migrate?

**PostgreSQL:** `AUTO_INCREMENT` vs `SERIAL`, `LIMIT` vs `OFFSET`, case sensitivity. Usually 20-30 queries need fixes. **PlanetScale:** Foreign key constraints disappear. Your data integrity goes to hell unless you enforce everything in app code. **MongoDB:** Everything. Your entire data model needs rethinking. Plan for a complete rewrite. **The annoying part:** Your ORM probably has MySQL-specific quirks that break with other databases. Budget time for this.

What's the stupidest mistake I can make?

**Choosing based on features instead of your team's ability to operate the database.** CockroachDB might be technically superior, but if nobody on your team understands distributed systems, you're screwed. **Second stupidest mistake:** Not testing the migration with real production data. Staging never has the weird edge cases that production data will reveal. **Actually smart approach:** Pick the boring option that your team can operate successfully. Usually that's PostgreSQL on RDS.

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MySQL Database Migration Decision Framework

Executive Summary

MySQL Cloud hosting costs are escalating while providing poor value. PostgreSQL migration is the recommended solution for 95% of applications, offering better features, lower costs, and superior community support.

Database Alternatives Analysis

PostgreSQL (Recommended)

Migration Complexity: Moderate (3-4 weeks)
Cost Impact: $3,600/year savings vs MySQL Cloud
Compatibility: 95% - requires syntax changes for LIMIT/OFFSET, AUTO_INCREMENT
Breaking Changes: 20-30 query updates typically required
Production-Ready: Yes
Team Size: All team sizes

Critical Implementation Notes:

Use pgloader for schema conversion (2-hour process for 500GB database)
AWS DMS enables minimal downtime migration
MySQL GROUP BY behavior differences may expose existing code bugs
Connection pooling with pgBouncer prevents connection issues

PlanetScale

Migration Complexity: Low (MySQL compatible)
Cost Threshold: $399/month after 1000 connections
Breaking Changes: Foreign keys permanently disabled, triggers non-functional
Production Limitations:

No referential integrity enforcement
Connection limit forces expensive tier upgrades
Deploy previews frequently fail
Team Size: Startups only (simple schemas)

Critical Warnings:

Vitess proxy strips foreign keys - data integrity becomes application responsibility
Lambda functions hit connection limits due to poor serverless connection pooling
Schema migration hangs require complete process restart

Supabase (PostgreSQL + Services)

Migration Complexity: PostgreSQL syntax requirements
Cost Progression: $25/month → $180/month at scale
Breaking Points:

Edge functions timeout on payloads >1MB
Real-time subscriptions fail at 100+ concurrent connections
Auth system conflicts with existing user tables
Team Size: Startups and MVPs (<10k users)

Performance Issues:

Row Level Security degrades complex query performance
Auto-scaling insufficient for serious traffic loads

MongoDB

Migration Complexity: Complete rewrite (6+ months)
Cost Escalation: $500/month baseline → $2,200/month due to connection pooling
Learning Curve: Severe - requires complete SQL mindset change
Critical Cost Trap: $1.10 per connection with poor Node.js connection management

Operational Failures:

No enforced schema creates versioning nightmares
Aggregation pipelines more complex than SQL joins
Index design requires distributed systems expertise

CockroachDB

Migration Complexity: PostgreSQL compatible syntax
Performance Impact: 2-3x slower than PostgreSQL for simple queries
Cost Structure: $100/month minimum → $2,000/month production
Use Case: Multi-region financial applications requiring ACID guarantees
Team Size: Enterprise only (50+ people)

Performance Characteristics:

Complex joins: 10+ second execution times
Automatic sharding often selects suboptimal shard keys
Distributed transactions add significant latency overhead

Aurora MySQL

Migration Complexity: Zero (MySQL compatibility)
Cost Model: $80/month minimum billing even when paused
Serverless Reality:

v1: 30-second cold starts, random pausing
v2: Improved but premium pricing for RDS features
Lock-in Risk: AWS ecosystem dependency

Migration Execution Framework

Pre-Migration Assessment

Schema Complexity Analysis
- Count stored procedures (500+ indicates MySQL retention)
- Identify foreign key dependencies
- Catalog custom MySQL functions
Performance Baseline
- Document current query execution times
- Measure connection pool utilization
- Record monthly cost breakdown

PostgreSQL Migration Process

Timeline: 2-4 weeks for competent teams
Downtime: 4 hours (optimizable to <1 hour)

Phase 1: Schema Conversion

mysqldump --no-data database_name > schema.sql
pgloader mysql://source postgresql://target

Phase 2: Query Compatibility

AUTO_INCREMENT → SERIAL conversions
LIMIT vs OFFSET syntax updates
Case sensitivity adjustments

Phase 3: Application Updates

Django model field changes (AutoField updates)
Connection string modifications
ORM-specific MySQL quirks resolution

Phase 4: Cutover

AWS DMS for minimal downtime
Connection pool reconfiguration
Performance monitoring validation

Cost-Benefit Analysis

Monthly Cost Comparison (Production Scale)

Solution	Base Cost	Scale Cost	Hidden Costs
MySQL Cloud	$680	Surprise scaling bills	Oracle licensing increases
PostgreSQL RDS	$420	Predictable scaling	None significant
PlanetScale	$39	$399 at 1000 connections	Loss of data integrity
Supabase	$25	$180 at traffic scale	Limited enterprise features
CockroachDB	$100	$2000+ production	Performance degradation
MongoDB Atlas	$500	$2200+ (connection pooling)	Expertise requirements

Team Size Recommendations

Startup (2-10 people):

Primary: Supabase (PostgreSQL + services)
Alternative: Neon (serverless PostgreSQL)
Avoid: CockroachDB, self-hosted solutions

Scale-up (10-50 people):

Primary: PostgreSQL RDS
Alternative: TiDB (MySQL compatibility)
Budget option: Aurora (AWS integration)

Enterprise (50+ people):

Global apps: CockroachDB (multi-region ACID)
AWS shops: Aurora (enterprise compliance)
Document storage: MongoDB Atlas (with proper expertise)

Critical Decision Factors

Technical Compatibility

PostgreSQL: 95% compatible, 20-30 query modifications required
PlanetScale: 100% MySQL compatible but loses foreign keys permanently
MongoDB: 0% compatible, complete application rewrite necessary

Operational Complexity

Managed PostgreSQL: Standard database administration
CockroachDB: Requires distributed systems expertise
MongoDB: Demands NoSQL data modeling skills

Cost Predictability

Most Predictable: PostgreSQL RDS, Aurora
Moderate Risk: Supabase, Neon
High Risk: PlanetScale (connection limits), MongoDB (connection pooling)

Failure Scenarios

PostgreSQL Migration Failures:

ORM compatibility issues (2-3 days additional work)
Complex stored procedure conversion (weeks of effort)
Performance regression on specific queries (optimization required)

PlanetScale Adoption Failures:

Data integrity issues from missing foreign keys
Expensive tier upgrades due to connection limits
Loss of advanced database features (triggers, stored procedures)

MongoDB Migration Failures:

6-month development timeline extensions
$2000+ monthly bills from poor connection management
Complete data model redesigns mid-project

Implementation Checklist

Pre-Migration Validation

Export production schema with mysqldump --no-data
Test pgloader conversion on sample data
Identify application queries requiring syntax updates
Validate ORM compatibility with target database
Establish performance baselines for critical queries

Migration Execution

Set up target database environment
Configure connection pooling (pgBouncer for PostgreSQL)
Execute schema conversion with pgloader
Update application configuration and connection strings
Deploy application changes with database syntax fixes
Monitor performance and connection utilization

Post-Migration Validation

Verify data integrity with row counts and checksums
Confirm query performance meets baseline requirements
Test connection pooling under load
Validate backup and recovery procedures
Monitor costs for first billing cycle

Resource Requirements

Technical Expertise

PostgreSQL: Standard SQL knowledge sufficient
MongoDB: 3-6 months NoSQL learning curve
CockroachDB: Distributed systems understanding required

Time Investment

PostgreSQL migration: 3-4 weeks competent team
MongoDB migration: 6+ months complete rewrite
PlanetScale adoption: 1 week setup, 3 months data integrity fixes

Financial Investment

Migration costs: $10,000-50,000 professional services
Training costs: $5,000-15,000 for NoSQL transitions
Opportunity costs: 2-6 months delayed feature development

Success Metrics

Technical Metrics

Query performance maintenance or improvement
Zero data loss during migration
Connection stability under load
Backup/recovery procedure validation

Business Metrics

Monthly hosting cost reduction
Developer productivity maintenance
Reduced vendor lock-in risk
Improved feature development velocity

Risk Mitigation

Rollback procedures tested and documented
Parallel environment validation
Gradual traffic migration capability
24/7 support availability during cutover

Useful Links for Further Investigation

Useful Links (That Actually Help When You're Migrating)

Link	Description
pgloader.io	Actually converts your MySQL schema and data to PostgreSQL
pgloader GitHub	Source code and real usage examples
AWS DMS	If you need zero-downtime migration (works well enough)
Neon Pricing Calculator	Serverless PostgreSQL, honest about compute costs
AWS RDS Pricing	Complicated but at least comprehensive
PlanetScale Pricing	Looks cheap until you hit connection limits
PostgreSQL Manual	Actually comprehensive, not just pretty
PostgreSQL Community	Official PostgreSQL community resources and forums
sysbench	Standard database benchmark, gets real numbers
pgbench	Built into PostgreSQL, good for load testing
Apache Bench	Simple HTTP load testing for API endpoints
Percona Consulting	These guys know MySQL/PostgreSQL performance