KeyDB: The Reference Architecture for Multithreaded High-Performance Caching

TL;DR

Redis is the undisputed king of in-memory databases, but it has an architectural Achilles’ heel: it is single-threaded. Even on an expensive server with 64 cores, Redis uses only one core – the rest remain idle. KeyDB is a high-performance fork of Redis that breaks this shackle. With true multithreading, KeyDB utilizes the full hardware power, offers up to 5x more throughput, and remains 100% compatible. Those who use KeyDB scale vertically instead of horizontally, saving themselves complex cluster architectures.

1. The Architectural Principle: Multithreading vs. Single Core

The design of Redis comes from a time when CPUs were getting faster (more GHz), not wider (more cores).

• The Redis Problem: All requests must go through a single queue (event loop) on a single CPU core. Under high load, this one core becomes a bottleneck, while 95% of the server is idle.
• The KeyDB Solution: KeyDB introduces multithreading. It can process requests in parallel on multiple CPU cores. The result is a massive increase in operations per second (OPS) without any change in latency.

2. Core Feature: Active-Active Replication (Multi-Master)

In classic Redis setups, there is a “master” (writes) and several “replicas” (read). If the master fails, there is downtime until a new one is elected (failover).

KeyDB enables true active-active hosting.

• High Availability: You can operate two KeyDB instances that both accept read and write access and synchronize with each other. If one fails, traffic seamlessly continues over the other.
• Geographic Distribution: You can have one instance in Frankfurt and one in the USA. Users write to their local node, and KeyDB synchronizes the data in the background.

3. Simplicity through “Drop-in Replacement”

Switching from Redis to KeyDB often requires not a single line of code change.

KeyDB is fully compatible with the Redis protocol, modules, and rdb files.

• Compatibility: Your application “thinks” it is talking to Redis. You use the same client libraries, the same CLI tools, and the same commands.
• Simplified Scaling: Instead of immediately setting up a complex Redis cluster (sharding) when facing performance issues, you can simply scale “vertically” with KeyDB (larger server with more cores). This keeps the architecture drastically simpler.

4. Operating Models Compared: AWS ElastiCache (Redis) vs. ayedo Managed KeyDB

Here, it is decided whether you waste hardware or use it efficiently.

Scenario A: AWS ElastiCache for Redis (The Single-Core Brake)

ElastiCache is a solid service but suffers from Redis limits.

• Resource Waste: You rent a cache.r6g.4xlarge instance with 16 vCPUs. Redis effectively uses 1 vCPU for processing. You pay for hardware you cannot use.
• Cluster Compulsion: To get more performance, AWS forces you into “Cluster Mode Enabled” (sharding). This means data is distributed across many small nodes. This makes client libraries more complex, complicates transactions, and makes debugging a nightmare.
• Cost: Managed Redis is expensive. Due to the single-thread limitation, you often need more instances than necessary, multiplying the costs.

Scenario B: KeyDB with Managed Kubernetes by ayedo

In the ayedo app catalog, KeyDB is the turbo replacement for Redis.

• Hardware Efficiency: KeyDB uses all cores of your worker nodes. A single KeyDB pod can often do the work of an entire Redis cluster. This significantly reduces the infrastructure footprint.
• Active-Active: While AWS Global Datastore is expensive and complex, you enable active-active replication in KeyDB with a few config lines.
• Flash Storage (Tiering): KeyDB (in the Pro/Enterprise version, but also architecturally prepared) can use SSDs (flash) as storage extension. Cold data lands on the cheap SSD, hot data in the expensive RAM. Redis must keep everything in RAM.

Technical Comparison of Operating Models

FAQ: KeyDB & Caching Strategy

Is KeyDB really 100% compatible?

Yes. KeyDB strictly adheres to the Redis protocol. You can address KeyDB with redis-cli. Even Redis modules are supported. The switch is usually a simple replacement of the Docker image or the Helm chart.

When should I use KeyDB instead of Redis?

As soon as you notice that the CPU of a Redis node is stuck at 100% (on one core) while the rest of the server is bored. Or if you need an active-active architecture to completely eliminate downtimes during maintenance. For very small workloads, the difference is negligible, but under load, KeyDB is superior.

Do I need special RAM for KeyDB?

No. But KeyDB is more efficient in handling memory. With features like “Flash Tiering” (optional), KeyDB can even require less RAM than Redis, as it can offload data to fast NVMe SSDs without drastically degrading performance.

Is KeyDB open source?

Yes, KeyDB is available under an open license (BSD-3 like clause in newer versions / RSAL). It is a community-driven project that emerged as a direct response to stagnation in Redis core development.

Conclusion

In-memory databases should be fast and not limit the hardware. While Redis is stuck in the single-core era, KeyDB brings caching into the multicore era. Those who use AWS ElastiCache often pay for idle CPU cycles and buy scaling through unnecessary complexity (sharding). With KeyDB and the ayedo Managed Stack, you get the maximum performance from your infrastructure – simpler, faster, and more cost-effective.