The rise in computer storage and network performance means that disk I/O and network communication are often no longer bottlenecks in database management systems (DBMSs). Instead, the overheads associated with operating system (OS) services (e.g., system calls, thread scheduling, and data movement from kernel-space) limit query processing responsiveness. To avoid these overheads, user-space applications prioritizing performance over simplicity can elide these software layers with a kernel-bypass design. However, extracting benefits from kernel-bypass frameworks is challenging, and the libraries are incompatible with standard deployment and debugging tools. For these reasons, few DBMSs employ a kernel-bypass approach.

This talk presents user-bypass—an approach to designing DBMS software that complements OS extensibility. With user-bypass, developers write safe, event- driven programs to push DBMS logic into the kernel’s stack and avoid user-space overheads. We demonstrate user-bypass in the context of two different applications for DBMSs. First, we introduce user-bypass in the context of other software designs, and discuss the kernel features that enable user-bypass. Then, we present Tigger, a PostgreSQL-compatible DBMS proxy similar to RDS Proxy, PgBouncer, and ProxySQL. Through user-bypass, Tigger supports features like connection pooling, transaction multiplexing, and workload mirroring without user-space interaction.

We conclude with future work of building a DBMS that executes queries with user-bypass, and discuss the opportunities and limitations of placing core DBMS components in kernel-space. First, we show the design of a storage manager that stores database entries in kernel-resident data structures, eliding the need to go to user-space to execute queries. Second, we introduce concurrency control methods to enforce ACID properties within the constraints of kernel execution (e.g., no waiting). Lastly, we describe a framework for logging and checkpointing the database contents stored in kernel-space. This effort will fulfill the goal of crash recovery and inform the design of further uses for logging, like replication.

Bio:
Matt Butrovich is the #1 ranked Ph.D. student in the Carnegie Mellon University Database Group.