Shopify replaced Redis with MySQL for inventory reservations, achieving 10x scalability. The e-commerce giant's move challenges the conventional wisdom that Redis is necessary for high-throughput, low-latency operations.
Key facts
- Shopify replaced Redis with MySQL for inventory reservations
- System scales to 50,000 writes per second
- 10x throughput improvement after migration
- Single MySQL cluster replaced Redis infrastructure
- Migration eliminated cache invalidation and consistency issues
Shopify's engineering team published a detailed post explaining why they migrated from Redis to MySQL for their inventory reservations system. The system handles 50,000 writes per second after migration [According to Shopify Engineering].
The unique take: This is a rare case where a team moved away from Redis to a relational database for a latency-sensitive workload, contradicting the typical pattern of adopting Redis for caching and real-time operations. Shopify found that MySQL's InnoDB engine, with proper indexing and connection pooling, outperformed Redis for their specific reservation pattern — which involves complex transactions and strict consistency requirements.
How the migration worked
The Shopify team rewrote the reservation logic to use MySQL's transactional guarantees directly. They used a single MySQL cluster with read replicas for scaling reads, while writes go to the primary. The key optimization was using SELECT ... FOR UPDATE locks for atomic reservations, which Redis lacked without custom Lua scripting.
Results and operational impact
The migration eliminated Redis-related operational overhead: cache invalidation, data consistency issues between Redis and MySQL, and the need for a separate caching layer. The system now runs on a single MySQL cluster, reducing infrastructure complexity. Shopify reported 10x improvement in throughput and lower latency p99 [According to the source].
Broader implications
This move signals that for workloads requiring strong consistency and complex transactions, relational databases can outperform key-value stores. It's a reminder that Redis is not always the right tool, even for high-throughput systems. Shopify plans to open-source the migration tooling and benchmark results.
What to watch
Watch for Shopify's open-source release of migration tooling and benchmark results, expected in Q2 2026. Also track whether other high-throughput e-commerce platforms (e.g., Amazon, eBay) adopt similar patterns for reservation systems.
