Nicheloom

Market intelligence for builders — see what's gaining traction before it's crowded.

Ayder

HTTP-native durable event log written in C (curl as client)

Details

External ID
46604862
Source
HN
Company
—
Product
Ayder
Website domain
github.com
Launched
Jan. 13, 2026
Cohort
—
Upvotes
56
Upvotes percentile
0.8208168642951251
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

Hi HN,I built Ayder — a single-binary, HTTP-native durable event log written in C. The wedge is simple: curl is the client (no JVM, no ZooKeeper, no thick client libs).There’s a 2-minute demo that starts with an unclean SIGKILL, then restarts and verifies offsets + data are still there.Numbers (3-node Raft, real network, sync-majority writes, 64B payload): ~50K msg/s sustained (wrk2 @ 50K req/s), client P99 ~3.46ms. Crash recovery after SIGKILL is ~40–50s with ~8M offsets.Repo link has the video, benchmarks, and quick start. I’m looking for a few early design partners (any event ingestion/streaming workload).

Enrichment

Theme
developer infrastructure and monitoring utilities
Vertical
Horizontal
Function
Data infrastructure
Audience
Developer
AI stance
Not AI
Project type
Commercial product
Normalized one-liner
http-native durable event log system
Manually corrected
False

Could you build this?

No Writing a durable, crash-consistent event log in C that survives SIGKILL with zero data corruption requires deep systems programming, storage engine design, and Linux kernel I/O expertise.

What it would actually take: The architecture requires low-level C with custom append-only segment storage, WAL, write barriers, fsync synchronization, memory mapping, and a custom epoll-based HTTP server. The core difficulty lies in crash recovery semantics, byte-level offset durability without external consensus engines, and extensive Jepsen-style fault injection testing.

Discussion

20 comments analyzed.

Competitors mentioned: Kafka, Feed API spec

Concerns raised: Performance comparable to quickly-written Python implementations, Poor quality software with bad performance (Kafka mentioned as established alternative), Overhead with indirection on cloud platforms like Digital Ocean, Scheduler overhead in userspace implementation, README feels like LLM-generated marketingspeak rather than authentic documentation

Feature requests: HTTP Range headers for offset-based pagination, Event log consumption as standardized protocol across brokers, Mature client libraries and external specification to avoid bikeshedding, Simpler Makefile using implicit C compilation rules

Competitors

Other products that read as similar to this one — 70 launches clear the similarity bar, closest 8 shown.

Attention rank: #13 of 71 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 73 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a data infrastructure tool for Media & entertainment yet.