10x Database Throughput with io_uring and a Dual WAL

Building a complex database, the author experimented with io_uring and a dual WAL design to boost performance. Traditional WAL approaches (write-then-apply) bottleneck performance. By separating "intent to write" and "completion of write" into two WALs, and leveraging io_uring asynchronous I/O, a 10x throughput improvement was achieved. This design asynchronously writes intent, then completion records; recovery only applies operations with both intent and completion, ensuring data consistency. The author used Zig and the Poro project (an experimental key-value database) to validate this approach, highlighting the importance of hardware parallelism, batching, and flexible consistency models.