PostgreSQL, known for its robustness and ACID compliance, can also function as an efficient key-value store, potentially replacing Redis in certain scenarios. While Redis excels as an in-memory cache with ultra-fast read/write operations, Postgres offers persistence, complex querying, and reduced infrastructure overhead.
How to Use Postgres as a Key-Value Store
1. Unlogged Tables for Faster Writes
CREATE UNLOGGED TABLE key_value_store ( key TEXT PRIMARY KEY, value JSONB, expires_at TIMESTAMP );
Unlogged tables skip Write-Ahead Logging (WAL), improving write performance.
2. TTL (Time-To-Live) Implementation
DELETE FROM key_value_store WHERE expires_at < NOW();
Run this periodically or as part of your application logic.
3. Indexing for Faster Lookups
CREATE INDEX idx_key_value_store_key ON key_value_store (key);
4. Optimizing Performance
ALTER SYSTEM SET shared_buffers = '4GB'; -- Adjust based on RAM ALTER SYSTEM SET effective_cache_size = '12GB';
You Should Know:
- Benchmarking Postgres vs. Redis
- Redis: ~100,000+ ops/sec (in-memory)
- Postgres: ~10,000-50,000 ops/sec (disk-based, with optimizations)
- When to Use Postgres Instead of Redis?
- When you need persistence + caching in a single system.
- When simplifying infrastructure (no separate Redis instance).
- When ACID transactions are required alongside caching.
When to Stick with Redis?
- Ultra-low latency requirements (microseconds matter).
- Pub/Sub, Lua scripting, or atomic operations are needed.
- High-frequency writes where disk I/O becomes a bottleneck.
Practical Commands for Testing
- Redis Benchmark:
redis-benchmark -t set,get -n 100000 -q
- Postgres Benchmark (using
pgbench):pgbench -c 10 -j 2 -t 1000 -f test_script.sql
What Undercode Say:
Postgres is versatile, but it’s not a drop-in replacement for Redis. If your workload involves high-speed caching with frequent evictions, Redis (or Valkey, a Redis fork) remains superior. However, for simpler architectures where reducing moving parts is a priority, Postgres can be a viable alternative.
Expected Output:
A hybrid approach might work best—using Postgres for persistent data and Redis for high-speed caching—depending on the use case.
Prediction:
As Postgres continues to improve its in-memory and caching capabilities, we may see more developers adopting it for lightweight caching, especially in smaller-scale applications where infrastructure simplicity is valued over raw speed.
References:
Reported By: Milan Jovanovic – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
