mpenet

mpenet / k7

Public

A high-performance disk-backed queue for Clojure

19
0
100% credibility
Found Apr 07, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Clojure
AI Summary

k7 is a high-performance, disk-backed message queue library designed for fast and reliable enqueueing and consumption of messages in Clojure applications.

How It Works

1
🔍 Discover k7

You hear about k7, a super-fast tool for lining up and handling tons of messages reliably on your computer's storage.

2
🛠️ Add to your project

You easily bring k7 into your existing work setup with a simple addition.

3
📁 Set up storage

You pick a folder where k7 will keep all your messages safe and organized.

4
🚀 Send messages

You start pouring messages into the queue, feeling the speed as it handles millions without breaking a sweat.

5
👥 Launch workers

You create groups of workers that grab messages in smart batches to process them.

6
⚡ Process and confirm

Workers pull messages, do their job, and mark them done, with everything staying reliable even if something crashes.

🎉 Blazing success

Your app now handles messages at incredible speeds, safely and without losing a beat.

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AI-Generated Review

What is k7?

k7 delivers a disk-backed message queue for Clojure apps, handling enqueue at 20M msg/s and poll+ack at 6.5M msg/s on Apple M1 hardware. It persists messages durably with crash recovery, supports single-writer multiple consumer groups, and offers ack/nack/seek for at-least-once delivery. Developers get a simple API via Clojars: open a queue on a directory, enqueue byte arrays, poll batches with timeouts, and manage cursors per group—all with tunable fsync strategies from async to full sync.

Why is it gaining traction?

In a world of high performance GitHub projects like C++ queues or Java persistence layers, k7 stands out with zero-copy reads, zero-alloc enqueues, and adaptive batching that keep latency under 200ns at scale. Its core.async helpers like producer-chan and consumer-group-chan make threading painless without hidden locks. Devs dig the raw throughput on plain disks, rivaling Chronicle Queue but tailored for Clojure workflows.

Who should use this?

Clojure backend engineers building event-driven services, real-time analytics pipelines, or microservices with high-ingest queues. Ideal for teams needing Kafka-like persistence without ops overhead, especially single-producer systems like log appenders or task distributors. Skip if you require multi-writer threads out of the box—use its locking or dedicated writer patterns.

Verdict

Grab k7 for perf-critical Clojure queues if you're okay with WIP status (19 stars, 1.0% credibility)—docs are solid, benchmarks transparent, tests run clean, but back up data. Strong start for high performance Clojure on GitHub; watch for multi-producer polish.

(198 words)

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