Redis Is Not Free Performance

Why adding Redis often shifts complexity instead of removing it and what that means for correctness.

You’re building an application.
You care about fast pages.
You want to protect your database.
You don’t want to keep recalculating the same results on every request.
So you introduce Redis.
Responses speed up.
Latency drops.
The database finally gets a break.
You deploy feeling confident.
Performance feels “solved.”
Then the product evolves.
User traffic grows.
Features multiply.
Caching starts to look like the obvious solution everywhere.
And slowly, production feels… off.
Some users see outdated data.
Counts stop lining up.
Memory usage keeps rising for Redis servers.
A single cache miss suddenly overwhelms the database.
Nothing is outright failing.
But the system feels brittle.
What’s really happened is simple.
You didn’t eliminate complexity.
You relocated it.
Redis isn’t “free performance.”

It’s:
• Another data layer
• With its own structure
• Its own edge cases
• And its own failure scenarios

That fundamentally changes your system.

Before Redis: App → Database
One authority.
Clear consistency.

After Redis: App → Redis → Database

Now Redis is:
• The primary read path
• A buffer in front of the database
• A possible source of stale or incorrect data
• A core part of system correctness
Cache invalidation stops being theoretical.

You now have to decide:
• What should expire
• What must stay consistent
• What’s allowed to be slightly out of date

Redis won’t guide those choices.
It will faithfully do exactly what you configure — even if that leads to subtle bugs over time.

The fundamentals of performance don’t change.

Key design matters.
TTL decisions matter.
Data shape matters.
Redis helps avoid redundant work.
It reduces unnecessary database pressure.
But it doesn’t remove accountability.

You still need to:
• Choose carefully what gets cached
• Understand read and write behavior
• Design for cache misses
• Treat Redis as an optimization, not a system of record

Redis enables fast systems, no doubt. Making them correct, stable,
and maintainable over time, well
that responsibility never leaves you.