Database Selection Guide: PostgreSQL vs MySQL vs SQLite vs MongoDB

Choosing the right database affects your application’s performance, scalability, and development experience. This guide compares major database options using official documentation and real-world considerations.

Database Categories

Databases fall into two main categories:

Relational Databases (SQL)

• Store data in tables with rows and columns
• Use SQL (Structured Query Language)
• Enforce relationships through foreign keys
• ACID compliant (Atomicity, Consistency, Isolation, Durability)
• Examples: PostgreSQL, MySQL, SQLite, SQL Server

Non-Relational Databases (NoSQL)

• Store data in various formats (documents, key-value, graphs)
• Flexible schemas
• Designed for horizontal scaling
• Various consistency models
• Examples: MongoDB, Redis, Cassandra, DynamoDB

Comparison Overview

Database	Type	Best For	License
PostgreSQL	Relational	Complex queries, data integrity	PostgreSQL License (permissive)
MySQL	Relational	Read-heavy apps, web applications	GPL or Commercial
SQLite	Relational	Embedded, mobile, small apps	Public Domain
MongoDB	Document	Flexible schemas, rapid development	SSPL
Redis	Key-Value	Caching, sessions, real-time	BSD

PostgreSQL

PostgreSQL is an advanced open-source relational database known for standards compliance and extensibility.¹

Key Features

From Official Documentation:¹

• Full ACID compliance
• Advanced data types (JSON, arrays, hstore, geometric)
• Full-text search built-in
• Extensible (custom types, functions, operators)
• Window functions and CTEs
• Materialized views
• Table partitioning
• Parallel query execution

Performance Characteristics

PostgreSQL handles complex queries efficiently:

Workload	Performance
Complex JOINs	Excellent
Write-heavy	Good
Read-heavy	Excellent
Full-text search	Good (built-in)
JSON queries	Excellent
Concurrent writes	Excellent (MVCC)

Data Types

PostgreSQL supports numerous data types:²

Numeric: integer, bigint, numeric, real, double precision Text: char, varchar, text Binary: bytea Date/Time: timestamp, date, time, interval Boolean: boolean JSON: json, jsonb (binary JSON with indexing) Arrays: any[] (arrays of any type) Geometric: point, line, circle, polygon Network: inet, cidr, macaddr UUID: uuid Custom: CREATE TYPE for custom types

When to Choose PostgreSQL

Choose PostgreSQL when:

• Data integrity is critical
• You need complex queries with JOINs
• You’re storing JSON but want SQL capabilities
• You need full-text search
• You want extensibility (PostGIS, etc.)
• You need advanced features (CTEs, window functions)

Examples:

• Financial applications
• E-commerce with complex inventory
• Geospatial applications (with PostGIS)
• Analytics platforms
• Most production web applications

PostgreSQL Hosting Options

Provider	Type	Starting Price
Supabase3	Managed	Free tier, $25/mo Pro
Neon4	Serverless	Free tier, usage-based
Railway	Managed	Usage-based (~$5/mo)
Render	Managed	$7/mo
AWS RDS	Managed	~$15/mo
DigitalOcean	Managed	$15/mo
Self-hosted	DIY	Server costs only

MySQL

MySQL is the world’s most popular open-source relational database, now owned by Oracle.⁵

Key Features

From Official Documentation:⁵

• ACID compliance (with InnoDB engine)
• Replication (source-replica, group replication)
• Partitioning
• Stored procedures and triggers
• Full-text search (InnoDB)
• JSON support (MySQL 5.7+)
• Window functions (MySQL 8.0+)

Performance Characteristics

Workload	Performance
Simple queries	Excellent
Read-heavy	Excellent
Write-heavy	Good
Complex JOINs	Good
Replication	Excellent

MySQL vs PostgreSQL

Feature	MySQL	PostgreSQL
Default storage	InnoDB	Single engine
JSON support	Good	Excellent (jsonb)
Full-text search	Good	Better
Replication	Easier setup	More options
Standards compliance	Good	Excellent
Extensions	Limited	Extensive
Window functions	Yes (8.0+)	Yes (earlier)
CTEs	Yes (8.0+)	Yes (earlier)

When to Choose MySQL

Choose MySQL when:

• You need simple, fast reads
• Your team has MySQL expertise
• You’re using frameworks with strong MySQL support (Laravel, Rails)
• You need easy replication setup
• You’re hosting WordPress or similar PHP apps

Examples:

• WordPress sites
• Read-heavy web applications
• PHP/Laravel applications
• Simple CRUD applications

SQLite

SQLite is a self-contained, serverless SQL database engine.⁶

Key Features

From Official Documentation:⁶

• Zero configuration required
• Single file storage
• Serverless (no separate process)
• Cross-platform
• ACID compliant
• Full SQL support (most of SQL-92)
• Small footprint (~700 KB)

Architecture

Unlike client-server databases, SQLite:

• Reads and writes directly to disk files
• Runs in the same process as the application
• Requires no network configuration
• Uses file locking for concurrent access

Limitations

SQLite has intentional limitations:⁷

Limitation	Details
Max database size	281 TB (theoretical)
Concurrent writes	One at a time (locking)
Max row size	~1 GB
Network access	Not designed for it
User management	None (file permissions only)

When to Choose SQLite

Choose SQLite when:

• Building mobile applications
• Creating embedded systems
• Developing and testing locally
• Building single-user desktop apps
• Need a simple, portable database
• Traffic is low to medium

Choose something else when:

• Multiple servers need access
• High write concurrency required
• Need user access control
• Building high-traffic web apps

SQLite in Production

SQLite can work in production for specific use cases:⁸

Works well:

• Low to medium traffic websites
• Read-heavy applications
• Edge deployments (Cloudflare D1, LiteFS)
• Mobile apps

Use caution:

• High-traffic APIs
• Multiple application instances
• Write-heavy workloads

MongoDB

MongoDB is a document-oriented NoSQL database that stores data in flexible, JSON-like documents.⁹

Key Features

From Official Documentation:⁹

• Document model (BSON format)
• Flexible schemas
• Horizontal scaling (sharding)
• Replication with automatic failover
• Aggregation framework
• Full-text search (Atlas Search)
• ACID transactions (4.0+)

Document Model

MongoDB stores data as documents:

{
  "_id": ObjectId("..."),
  "name": "John Doe",
  "email": "john@example.com",
  "orders": [
    {
      "product": "Widget",
      "quantity": 2,
      "price": 29.99
    }
  ],
  "address": {
    "street": "123 Main St",
    "city": "Boston"
  }
}

When Documents Work Well

Good fit:

• Nested/hierarchical data
• Varying attributes across documents
• Rapid prototyping
• Content management systems
• Real-time analytics

Challenging:

• Highly relational data
• Complex transactions across documents
• Strong consistency requirements

MongoDB vs SQL Databases

Aspect	MongoDB	SQL Databases
Schema	Flexible	Fixed (enforced)
Relationships	Embedded or referenced	Foreign keys
Transactions	Supported (4.0+)	Native, mature
Scaling	Horizontal (sharding)	Vertical (usually)
Query language	MongoDB Query Language	SQL
Joins	$lookup (limited)	Native, optimized

When to Choose MongoDB

Choose MongoDB when:

• Schema will change frequently
• Data is naturally document-shaped
• You need horizontal scaling from day one
• Building content management or catalogs
• Rapid prototyping is priority

Consider SQL instead when:

• Data has many relationships
• You need complex joins
• Strong consistency is critical
• Team has SQL expertise

MongoDB Hosting Options

Provider	Type	Starting Price
MongoDB Atlas10	Official managed	Free tier, $57/mo dedicated
Railway	Managed	Usage-based
DigitalOcean	Managed	$15/mo
Self-hosted	DIY	Server costs only

Redis

Redis is an in-memory data structure store used as a database, cache, and message broker.¹¹

Key Features

From Official Documentation:¹¹

• In-memory storage (extremely fast)
• Data structures: strings, hashes, lists, sets, sorted sets
• Pub/sub messaging
• Lua scripting
• Transactions (MULTI/EXEC)
• Persistence options (RDB, AOF)
• Clustering and replication

Use Cases

Redis excels at specific use cases:

Use Case	How Redis Helps
Caching	Sub-millisecond reads
Sessions	Fast session storage
Rate limiting	Atomic counters
Leaderboards	Sorted sets
Real-time	Pub/sub messaging
Queues	List operations

Redis as Primary Database

Redis can be a primary database for specific patterns:

Works well as primary:

• Session storage
• Caching layers
• Real-time features
• Simple key-value needs

Not recommended as primary:

• Complex relational data
• Large datasets (limited by memory)
• Complex queries

Redis Persistence

Redis offers persistence options:¹²

RDB (Snapshotting):

• Point-in-time snapshots
• Good for backups
• Some data loss on crash

AOF (Append Only File):

• Logs every write operation
• Better durability
• Larger file size

Hybrid:

• Combine both approaches
• Best of both worlds

Specialized Databases

Time-Series Databases

For time-stamped data (metrics, IoT, logs):

Database	Use Case
InfluxDB	Metrics, monitoring
TimescaleDB	PostgreSQL extension
Prometheus	Monitoring

Graph Databases

For relationship-heavy data:

Database	Use Case
Neo4j	Complex relationships
Amazon Neptune	AWS-managed graph
ArangoDB	Multi-model

Search Databases

For full-text search:

Database	Use Case
Elasticsearch	Search, log analysis
Meilisearch	Simple search
Typesense	Fast typo-tolerant search

Decision Framework

By Application Type

Application	Recommended Database
Traditional web app	PostgreSQL
Mobile app	SQLite
Content management	PostgreSQL or MongoDB
E-commerce	PostgreSQL
Real-time/gaming	PostgreSQL + Redis
Analytics	PostgreSQL or ClickHouse
IoT/time-series	TimescaleDB or InfluxDB
Social network	PostgreSQL + graph (maybe)

By Team Experience

If your team knows…	Consider…
SQL	PostgreSQL or MySQL
JavaScript	MongoDB (lower barrier)
PHP	MySQL (common pairing)
Python	PostgreSQL (excellent drivers)

By Scale Requirements

Scale	Recommendation
Single server	PostgreSQL, MySQL, SQLite
Multiple servers, reads	PostgreSQL with replicas
Massive write scale	Consider sharding or NoSQL
Global distribution	CockroachDB, Cassandra, DynamoDB

Best Practices

General Database Guidelines

1. Start with PostgreSQL - It handles most use cases well
2. Use migrations - Track schema changes in version control
3. Index appropriately - Index columns used in WHERE and JOIN
4. Monitor queries - Use EXPLAIN to find slow queries
5. Backup regularly - Test restores periodically
6. Use connection pooling - PgBouncer, ProxySQL, or built-in

ORM Considerations

Modern ORMs work with multiple databases:

ORM	Language	Databases
Prisma	TypeScript	PostgreSQL, MySQL, SQLite, MongoDB
Drizzle	TypeScript	PostgreSQL, MySQL, SQLite
SQLAlchemy	Python	Most SQL databases
Django ORM	Python	PostgreSQL, MySQL, SQLite
Sequelize	JavaScript	PostgreSQL, MySQL, SQLite

When to Use Multiple Databases

Some applications benefit from polyglot persistence:

Primary data → PostgreSQL
Caching → Redis
Full-text search → Elasticsearch
Sessions → Redis
Analytics → ClickHouse

Only add complexity when genuinely needed.

Summary Recommendations

For Most Projects: PostgreSQL

PostgreSQL is the safe default choice:

• Handles relational and JSON data
• Scales to millions of rows
• Rich ecosystem and tooling
• Free and open source
• Excellent hosting options

For Specific Needs

Need	Database
Mobile/embedded	SQLite
Flexible schemas	MongoDB
Caching/sessions	Redis
Time-series	TimescaleDB
Full-text search	Meilisearch or Elasticsearch

Avoid Premature Optimization

Start simple:

1. Begin with PostgreSQL (or MySQL if preferred)
2. Add Redis for caching when needed
3. Add specialized databases only when requirements demand

Most applications never need horizontal scaling or NoSQL. A well-tuned PostgreSQL instance handles significant load.

Further Reading

• Related: Modern Tech Stack Guide
• Related: Hosting Platform Comparison
• PostgreSQL Documentation
• MySQL Documentation
• SQLite Documentation
• MongoDB Documentation
• Redis Documentation

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References

Footnotes

1. PostgreSQL Global Development Group. “PostgreSQL: About.” https://www.postgresql.org/about/ ↩ ↩²

2. PostgreSQL Global Development Group. “PostgreSQL: Documentation - Data Types.” https://www.postgresql.org/docs/current/datatype.html ↩

3. Supabase. “Pricing.” https://supabase.com/pricing ↩

4. Neon. “Pricing.” https://neon.tech/pricing ↩

5. Oracle Corporation. “MySQL Documentation.” https://dev.mysql.com/doc/ ↩ ↩²

6. SQLite Consortium. “About SQLite.” https://www.sqlite.org/about.html ↩ ↩²

7. SQLite Consortium. “Appropriate Uses For SQLite.” https://www.sqlite.org/whentouse.html ↩

8. SQLite Consortium. “SQLite As An Application File Format.” https://www.sqlite.org/appfileformat.html ↩

9. MongoDB, Inc. “What is MongoDB?” https://www.mongodb.com/docs/manual/introduction/ ↩ ↩²

10. MongoDB, Inc. “MongoDB Atlas Pricing.” https://www.mongodb.com/pricing ↩

11. Redis Ltd. “Introduction to Redis.” https://redis.io/docs/about/ ↩ ↩²

12. Redis Ltd. “Redis Persistence.” https://redis.io/docs/management/persistence/ ↩