Comprehensive comparison between a traditional relational database and an in-memory data structure store. Understand when to use each technology and how they can complement each other in modern applications.
Relational Database
In-Memory Store
| Aspect | PostgreSQL | Redis |
|---|---|---|
| Primary Use Case | Primary database | Cache/Session store |
| Data Model | Relational + JSON | Key-value + data structures |
| Storage | Persistent (disk) | In-memory (optional persistence) |
| Query Language | SQL | Redis commands |
| ACID Compliance | Full ACID | Limited |
| Performance | Fast (disk-based) | Extremely fast (memory) |
| Data Size | Large datasets | Limited by RAM |
Redis significantly outperforms PostgreSQL for simple key-value reads.
Redis provides much higher write throughput due to in-memory operations.
PostgreSQL excels at complex queries, joins, and analytical operations.
CREATE TABLE users (
id SERIAL PRIMARY KEY,
profile JSONB,
tags TEXT[],
created_at TIMESTAMP DEFAULT NOW()
);# String
SET user:1000:name "John Doe"
# Hash
HSET user:1000 name "John" age 30
# List
LPUSH notifications "New message"
# Set
SADD user:tags "developer" "redis"Generally no. While Redis can persist data, it lacks ACID guarantees, complex query capabilities, and data relationships that are essential for most applications. Redis is best used as a cache, session store, or for specific real-time use cases alongside a primary database like PostgreSQL.
Yes, this is a common and effective pattern. Use PostgreSQL as your primary database for persistent, structured data and Redis for caching, sessions, and real-time features. This combination provides both reliability and performance.
Redis is significantly faster for simple operations due to its in-memory nature, achieving 100K+ operations per second. PostgreSQL is faster for complex queries and provides better performance for analytical workloads. The choice depends on your specific use case.
PostgreSQL can handle terabytes of data limited primarily by disk space. Redis is limited by available RAM, typically handling gigabytes to hundreds of gigabytes. For large datasets, PostgreSQL is more suitable, while Redis excels with smaller, frequently accessed data.
Redis offers persistence options (RDB snapshots and AOF logging), but it's primarily designed for speed over durability. Some data loss is possible during crashes. For critical data that cannot be lost, use PostgreSQL as the primary store and Redis for caching.
No, Redis doesn't support SQL or complex queries like joins, aggregations, or subqueries. Redis operations are focused on simple key-value access and data structure manipulation. For complex queries, use PostgreSQL.