Zig-Powered Redis Clone Hits 95% of Original Performance: Lessons from a Web Developer's Systems Journey

When Charles Fonseca set out to build Zedis—a Redis clone in Zig—as a web developer diving into systems programming, he expected a learning curve. He didn't anticipate nearly matching one of the world's most optimized databases. Recent benchmarks reveal Zedis now handles 1 million requests at 95% of Redis' throughput, a milestone demonstrating Zig's potential for high-performance systems.

The Parsing Bottleneck That Surprised Everyone

Initial flame graphs exposed a shocking inefficiency: 75% of execution time was consumed by Parse.parse—the command interpretation layer—while core operations like Client.executeCommand used just 13%. For an in-memory database, this inversion was alarming. "For a Redis clone, this is backwards," Fonseca noted. "Parsing should be fast, and command execution should dominate."

perf tool analysis revealed deeper issues:

22.936s total elapsed time
15.761s user time
64.451s system time  # I/O-bound operations dominated

The system was drowning in syscalls, not computation.

Two Critical Fixes

1. I/O Revolution: From Byte-by-Byte to Buffered Brilliance
   The original implementation used readSliceShort, processing network input one painful byte at a time—catastrophic for Redis' protocol format:

// BEFORE (slow)
var b_buf: [1]u8 = undefined;
const bytes_read = try reader.readSliceShort(&b_buf);

// AFTER (fast)
var reader_buffer: [1024 * 8]u8 = undefined;
var sr = self.connection.stream.reader(&reader_buffer);
const line = reader.takeDelimiterInclusive('
');

Buffering 8KB chunks reduced syscalls by orders of magnitude, aligning with Redis' own approach.

2. Allocator Awakening
   Zig's default GeneralPurposeAllocator carried safety checks and mutex locks that crippled performance. Switching to leaner allocators (page_allocator or smp_allocator) slashed overhead:
   > "A significant amount of time was spent in mutex locks related to the allocator. In systems programming, you must understand your tools' internals." — Charles Fonseca

Benchmark Breakdown: 220K vs. 233K Requests/Second

Using redis-benchmark with 50 concurrent clients and 1M requests:

Latency metrics showed near-parity, with Zedis' p99 SET latency at 0.175ms vs. Redis' 0.143ms—remarkable for a learning project.

Why This Matters Beyond Benchmarks

Fonseca's journey underscores a paradigm shift: Modern languages like Zig empower non-systems experts to build high-performance infrastructure. His advice to fellow developers:

"Start small, make mistakes, profile them, fix them. You don't need to be a C wizard—just curious and persistent. Study giants like Redis, PostgreSQL, or TigerBeetle; their source is your syllabus."

While Zedis won't replace Redis tomorrow, it proves that with the right tools and tenacity, web developers can contribute to the infrastructure layer—and nearly match industry titans. As Fonseca signs off: "This might be Zedis' sunset for now, but the dawn of accessible systems programming has just begun."

Source: Building a Redis Clone in Zig—Part 4 by Charles Fonseca