Redis Clone
A Redis-inspired distributed key-value store built to understand what replication actually costs — consistency models, persistence strategies, and the decisions that only reveal themselves under failure.
Deep Architectural Overview
Building a Redis clone isn't about reinventing a wheel. It's about understanding what's inside the wheel. This project was an exercise in distributed systems fundamentals — specifically how a system coordinates state across nodes when the network between them can't be trusted, and what you actually give up when you choose availability over consistency or vice versa.
The Technical Challenge
Most engineers who use Redis understand its API deeply but its internals loosely. That's fine until you're diagnosing a replication lag issue at 2am or choosing between RDB and AOF persistence for a workload that doesn't match the documentation examples. Building from scratch is the fastest way to develop genuine intuition about a system's guarantees.
Our Engineering Solution
The implementation covers the core semantics of a distributed key-value store: master-replica synchronization, transaction propagation for redundancy, and persistence strategies with configurable durability tradeoffs. Each design decision required understanding not just what Redis does but why — and what alternative choices would cost.
Tech Stack
- Java
- Distributed Systems
- Replication
- Persistence
Architectural Layout
- Replication Protocol: Master-replica synchronization implementing incremental replication log propagation with reconnection handling.
- Persistence Layer: Configurable snapshot and append-only file strategies with explicit tradeoffs between recovery speed and durability.
- Transaction Propagation: Ordered write propagation to replicas ensuring eventual consistency under normal operation and bounded divergence under partition.
- Command Processing: Single-threaded event loop model isolating command execution from I/O handling for predictable latency characteristics.
Key Impact
- Built a concrete mental model of distributed key-value store internals that informs how I design and debug production systems.
- The consistency model exploration clarified real tradeoffs that documentation usually abstracts — useful context for any system with replication requirements.
- Replication and persistence implementations revealed the gap between 'highly available' as a goal and as an engineering decision.