The Great Simplification: Why Your Database is Your Best Cache

For years, the "Standard Stack" followed a predictable pattern: Postgres for persistence, Redis for caching, and RabbitMQ or SQS for background jobs. We accepted this as the "Microservices Tax"—the price of doing business at scale.

But in 2026, we’re seeing a counter-movement. We’re realizing that for 90% of applications, the bottleneck isn't the database's speed; it's the architectural complexity of keeping all these systems in sync.

1. The "Single Source of Truth" Problem

When you introduce Redis, you introduce the Cache Invalidation nightmare. You now have two places where "the truth" lives. If your Redis write succeeds but your Postgres transaction fails, your system is in an inconsistent state. By using Postgres as your primary store and your high-speed lookup table (via Unlogged Tables), you gain Atomic Consistency.

2. Eliminating Distributed Transactions

When your queue (RabbitMQ) is separate from your database, you can't wrap a "job dispatch" and a "database update" in a single transaction. You end up needing the Outbox Pattern, which adds even more code to manage.

If your "jobs" table is just another table in Postgres, a simple DB::transaction ensures that the job is only created if the data is actually saved. No more "ghost jobs" that reference IDs that don't exist yet.

3. Postgres is Faster Than You Think

With the advent of NVMe storage and huge memory buffers, the "slowness" of disk-based databases has largely vanished for most workloads.

JSONB allows for schema-less "Redis-style" key-value storage.

LISTEN/NOTIFY handles real-time pub/sub.

SKIP LOCKED allows Postgres to act as a high-performance, concurrent queue without the risk of multiple workers grabbing the same task.

The "Garden" Takeaway The most senior move a developer can make is choosing not to add a tool. Every new service you add is another point of failure, another security surface area to patch, and another set of metrics to monitor. Before you reach for a specialized tool, ask: "Can I do this with a more clever SQL query first?"