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PostgreSQL vs MongoDB for SaaS

Problem

Choosing a database for a SaaS application with financial transactions, user data, and content storage.

Constraints

  • Need ACID transactions for payments
  • Complex queries and relationships
  • Team is familiar with SQL
  • May need to scale horizontally later

Options Comparison

PostgreSQL

Pros

  • Strong ACID guarantees (critical for payments)
  • Powerful SQL for complex queries
  • Excellent for relational data
  • JSON support (best of both worlds)
  • Mature ecosystem and tooling

Cons

  • Horizontal scaling is complex
  • Schema changes require migrations
  • Can be overkill for simple use cases

Best For

  • Financial applications (payments, credits)
  • Applications with complex relationships
  • When you need strong consistency
  • SaaS with user accounts and transactions

Worst For

  • Simple key-value lookups
  • Rapidly changing schemas
  • Very high write throughput (without sharding)

Scaling Characteristics

Reads:Excellent
Writes:Good
Horizontal:Fair

MongoDB

Pros

  • Flexible schema (easy to evolve)
  • Excellent horizontal scaling
  • Great for document-based data
  • Fast writes for simple operations

Cons

  • Weaker consistency guarantees
  • Complex queries are harder
  • No joins (must denormalize or application-level joins)
  • Transaction support is limited

Best For

  • Content management systems
  • Real-time analytics
  • IoT data
  • Catalogs with varying schemas

Worst For

  • Financial transactions
  • Complex relational queries
  • Strict ACID requirements

Scaling Characteristics

Reads:Excellent
Writes:Good
Horizontal:Excellent

Decision Framework

Consider: data structure (relational vs documents), consistency requirements, query complexity, team expertise, scaling needs

Recommendation

PostgreSQL for SaaS with payments and user data. MongoDB when you have clear document-based needs and need horizontal scaling from day one.

Reasoning

For AuthorAI and other SaaS products, PostgreSQL was the right choice because we needed ACID transactions for credit operations and payment processing. The relational model fits user accounts, transactions, and content metadata well. JSON columns handle flexible content data when needed.

Scaling Considerations

PostgreSQL: Use read replicas for read scaling, consider connection pooling (PgBouncer). MongoDB: Native sharding, but requires careful shard key selection. For most SaaS apps, PostgreSQL with proper indexing and read replicas scales well.