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Backend Storage Comparison

Detailed comparison of PostgreSQL, MongoDB, and SQLite for Pangolin metadata storage.

Quick Reference

Feature PostgreSQL MongoDB SQLite
Type Relational (SQL) Document (NoSQL) Relational (SQL)
Setup Medium Medium None
Production Ready ✅ Yes ✅ Yes ✅ Yes (small scale)
Persistence ❌ Catalog: No / ✅ Data: Yes ✅ Yes ✅ Yes
Scalability Vertical Horizontal Single machine
Concurrent Writes High Very High Low
Concurrent Reads Very High Very High Very High
ACID ✅ Full ✅ Full ✅ Full
Transactions ✅ Yes ✅ Yes ✅ Yes
Foreign Keys ✅ Yes ❌ No ✅ Yes
Indexes ✅ Advanced ✅ Advanced ✅ Basic
Full-Text Search ✅ Built-in ✅ Built-in ✅ FTS5
JSON Support ✅ JSONB ✅ Native ✅ JSON1
Branch Isolation ✅ Yes ✅ Yes (Native) ✅ Yes
Replication ✅ Built-in ✅ Built-in ❌ Manual
Sharding ⚠️ Extensions ✅ Built-in ❌ No
Backup ✅ pg_dump ✅ mongodump ✅ File copy
Point-in-Time Recovery ✅ Yes ✅ Yes (Atlas) ❌ No
Cloud Managed ✅ RDS, Azure, GCP ✅ Atlas, Azure, GCP ❌ No
Resource Usage Medium Medium Very Low
Memory Footprint ~100MB+ ~100MB+ ~10MB
Disk Space Medium Medium Low
Network Required ✅ Yes ✅ Yes ❌ No

Performance Comparison

Read Performance

Operation PostgreSQL MongoDB SQLite
Single row by ID Excellent Excellent Excellent
Range queries Excellent Excellent Excellent
Complex joins Excellent Good Good
Aggregations Excellent Excellent Good
Full table scan Good Good Excellent (small DBs)

Write Performance

Operation PostgreSQL MongoDB SQLite
Single insert Excellent Excellent Excellent
Bulk insert Excellent Excellent Good
Concurrent writes Excellent Excellent Poor
Updates Excellent Excellent Good
Deletes Excellent Excellent Good

Scalability

PostgreSQL

  • Vertical Scaling: Scale up to very large servers (1TB+ RAM)
  • Read Replicas: Multiple read-only replicas
  • Connection Pooling: PgBouncer for thousands of connections
  • Partitioning: Table partitioning for large datasets
  • Limitations: Single-master writes

MongoDB

  • Horizontal Scaling: Shard across multiple servers
  • Replica Sets: 3-50 members
  • Auto-Sharding: Automatic data distribution
  • Geographic Distribution: Multi-region clusters
  • Limitations: Complexity increases with sharding

SQLite

  • Single Machine: Limited to one server
  • File Size: Tested up to 281TB (theoretical)
  • Practical Limit: ~1TB with good performance
  • Limitations: No built-in replication or clustering

Cost Analysis

Development/Testing

Backend Setup Cost Ongoing Cost Complexity
PostgreSQL Medium $0 (local) Medium
MongoDB Medium $0 (local) Medium
SQLite None $0 None

Production (Small - <100 users)

Backend Monthly Cost Setup Time Maintenance
PostgreSQL (RDS t3.small) ~$30 1 hour Low
MongoDB (Atlas M10) ~$60 30 min Very Low
SQLite (EC2 t3.micro) ~$10 30 min Medium

Production (Medium - 100-1000 users)

Backend Monthly Cost Setup Time Maintenance
PostgreSQL (RDS t3.medium) ~$120 2 hours Low
MongoDB (Atlas M30) ~$250 1 hour Very Low
SQLite Not recommended - -

Production (Large - 1000+ users)

Backend Monthly Cost Setup Time Maintenance
PostgreSQL (RDS r5.xlarge) ~$500+ 4 hours Medium
MongoDB (Atlas M60+) ~$800+ 2 hours Low
SQLite Not recommended - -

Feature Support

Data Integrity

Feature PostgreSQL MongoDB SQLite
Foreign Keys ✅ Enforced ❌ Application-level ✅ Enforced
Unique Constraints ✅ Yes ✅ Yes ✅ Yes
Check Constraints ✅ Yes ⚠️ Limited ✅ Yes
NOT NULL ✅ Yes ⚠️ Schema validation ✅ Yes
Triggers ✅ Yes ✅ Yes ✅ Yes

Query Capabilities

Feature PostgreSQL MongoDB SQLite
SQL Support ✅ Full SQL ❌ MQL only ✅ Full SQL
Joins ✅ All types ⚠️ $lookup ✅ All types
Subqueries ✅ Yes ⚠️ Limited ✅ Yes
Window Functions ✅ Yes ⚠️ Limited ✅ Yes
CTEs ✅ Yes ❌ No ✅ Yes
Aggregations ✅ Yes ✅ Pipeline ✅ Yes

Advanced Features

Feature PostgreSQL MongoDB SQLite
Full-Text Search ✅ tsvector ✅ Text indexes ✅ FTS5
Geospatial ✅ PostGIS ✅ Built-in ⚠️ Extension
Multi-Tenancy ✅ SQL Isolation ✅ Collection Level ✅ SQL Isolation
RBAC / TBAC ✅ Built-in (Migs) ✅ Supported ✅ Built-in (Schema)
Audit Logging ✅ Automated ✅ Supported ✅ Automated
Federated Catalogs ✅ Supported ✅ Supported ✅ Supported
JSON Queries ✅ JSONB operators ✅ Native ✅ JSON1

Schema Management

Feature PostgreSQL MongoDB SQLite
Auto-Initialization ✅ Yes (sqlx migs) ⚠️ Partial (coll only) ✅ Yes (embedded)
Auto-Migrations ✅ Yes (sqlx) ❌ Manual ❌ Manual (reset req)
Manual Indexing ❌ Not required ✅ Essential ❌ Not required

Decision Matrix

Choose PostgreSQL If:

  • ✅ You need proven, enterprise-grade reliability
  • ✅ You want strong data integrity (foreign keys)
  • ✅ You're familiar with SQL
  • ✅ You need complex queries and joins
  • ✅ You want managed cloud options (RDS)
  • ✅ You're building a traditional web application
  • ✅ You need excellent tooling and ecosystem

Choose MongoDB If:

  • ✅ You need horizontal scalability
  • ✅ You prefer document-based data model
  • ✅ You want flexible schema evolution
  • ✅ You're building cloud-native applications
  • ✅ You need multi-region deployments
  • ✅ You're already using MongoDB
  • ✅ You want excellent managed service (Atlas)

Choose SQLite If:

  • ✅ You're developing locally
  • ✅ You need embedded database
  • ✅ You're deploying to edge/IoT devices
  • ✅ You want zero configuration
  • ✅ You have low concurrent write needs
  • ✅ You want minimal resource usage
  • ✅ You're prototyping or testing

Migration Paths

SQLite → PostgreSQL

Difficulty: Medium Tools: Custom scripts, pgloader Downtime: Required Use Case: Moving from development to production

SQLite → MongoDB

Difficulty: Hard Tools: Custom scripts Downtime: Required Use Case: Rare

PostgreSQL ↔ MongoDB

Difficulty: Hard Tools: Custom ETL Downtime: Required Use Case: Architectural change

Test Coverage

All backends have comprehensive test coverage:

Backend Tests Status
PostgreSQL Shared Regression Suite + Integration ✅ All passing
MongoDB Shared Regression Suite + Integration ✅ All passing
SQLite Shared Regression Suite + Integration ✅ All passing

Recommendations by Use Case

Startup/MVP

Recommended: SQLite → PostgreSQL

  • Start with SQLite for rapid development
  • Migrate to PostgreSQL when you have users

Enterprise

Recommended: PostgreSQL

  • Proven reliability
  • Excellent tooling
  • Strong consistency

Cloud-Native SaaS

Recommended: MongoDB

  • Horizontal scalability
  • Managed service (Atlas)
  • Multi-region support

Edge/IoT

Recommended: SQLite

  • Embedded
  • Low resources
  • No network required

Multi-Tenant SaaS

Recommended: PostgreSQL or MongoDB

  • Both provide excellent tenant isolation
  • PostgreSQL: Better for complex queries
  • MongoDB: Better for horizontal scaling

Conclusion

All three backends are production-ready and fully tested. Your choice should be based on:

  1. Deployment Environment: Cloud, on-prem, edge?
  2. Scale Requirements: How many users/requests?
  3. Team Expertise: SQL vs NoSQL familiarity?
  4. Budget: Managed vs self-hosted costs?
  5. Data Model: Relational vs document fit?

Default Recommendation: Start with SQLite for development, use PostgreSQL for production unless you specifically need MongoDB's horizontal scaling.

Next Steps