pgrust achieves 5-microsecond JIT compile times by bypassing LLVM

The creator of pgrust, a rewrite of PostgreSQL in Rust, has developed a custom Just-In-Time (JIT) compiler capable of compiling code in approximately 5 microseconds. This optimization aims to remove the performance bottlenecks typically associated with dynamic code generation in database engines.

To achieve these speeds, the developer bypassed the standard industry reliance on LLVM or the generation of C/C++ code, both of which introduce significant compilation latency. Instead, the pgrust JIT compiler targets machine assembly directly. According to the author of malisper.me, this process was facilitated by AI assistance, which lowered the technical barrier to writing a custom assembly emitter. By eliminating the intermediate layers of traditional compiler toolchains, the system can generate optimized machine code almost instantaneously.

The JIT Compilation Tax

Historically, implementing fast JIT compilation in databases has been a significant engineering challenge due to the deep assembly knowledge required. Most modern database systems have opted for LLVM, which provides powerful, high-level optimizations but comes with a heavy "compilation tax." For many short-running queries, the time spent compiling the code via LLVM can exceed the time saved by executing the optimized binary, often making JIT impractical for a wide range of real-world workloads.

Implications for Database Architecture

Reducing compilation time to the microsecond level changes the trade-off calculation for query optimization. When the overhead is negligible, a database can generate specialized machine code on-the-fly for nearly any query without risking a performance penalty. This approach suggests a shift in how new database engines might be constructed, moving away from general-purpose compiler frameworks in favor of lean, targeted emitters.

The Role of AI in Systems Programming

Beyond the performance gains, the project highlights a growing trend in systems programming: the use of large language models to handle low-level architectural tasks. "Now, with the use of AI, it’s easier than ever to write a JIT compiler with fast compile times by directly targeting assembly," stated the author of malisper.me. This suggests that AI may enable smaller teams to implement complex, low-level optimizations that were previously the sole domain of large corporate engineering teams with specialized compiler experts.

While the technical implementation of the 5μs compiler is documented, the broader impact on pgrust's overall performance relative to other production databases remains to be independently verified through third-party benchmarking.