Nicheloom

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

Qlog

grep for logs, but 100x faster

Details

External ID
47253193
Source
HN
Company
—
Product
Qlog
Website domain
github.com
Launched
March 4, 2026
Cohort
—
Upvotes
17
Upvotes percentile
0.7103321033210332
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

I built qlog because I got tired of waiting for grep to search through gigabytes of logs.qlog uses an inverted index (like search engines) to search millions of log lines in milliseconds. It's 10-100x faster than grep and way simpler than setting up Elasticsearch.Features: - Lightning fast indexing (1M+ lines/sec using mmap) - Sub-millisecond searches on indexed data - Beautiful terminal output with context lines - Auto-detects JSON, syslog, nginx, apache formats - Zero configuration - Works offline - Pure PythonExample: qlog index './logs/*/*.log' qlog search "error" --context 3I've tested it on 10GB of logs and it's consistently 3750x faster than grep. The index is stored locally so repeated searches are instant.Demo: Run `bash examples/demo.sh` to see it in action.GitHub: https://github.com/Cosm00/qlogPerfect for developers/DevOps folks who search logs daily.Happy to answer questions!

Enrichment

Theme
developer infrastructure and monitoring utilities
Vertical
Horizontal
Function
Observability & eval
Audience
Developer
AI stance
—
Project type
Commercial product
Normalized one-liner
fast log search tool
Manually corrected
False

Could you build this?

Partial A toy inverted index is simple to write, but creating a production CLI that searches gigabytes of logs 10-100x faster than ripgrep requires specialized knowledge of low-level systems and information retrieval algorithms.

What it would actually take: Typically written in Rust or C++ using memory-mapped I/O (`mmap`), finite state transducers (FST) for term dictionaries, and compressed inverted lists (such as Roaring bitmaps or SIMD-PFor). The performance gap over grep comes from cache-aware data structures, lockless multi-threaded segment merges, and hardware-accelerated bitwise operations.

Discussion

20 comments analyzed.

Competitors mentioned: Elasticsearch/ELK stack, Splunk, Loki, Grafana, ripgrep

Concerns raised: Missing features compared to mature observability stacks (e.g., graphing log match counts over time by source node), Not suitable for multi-machine/service debugging at scale or production outages with multiple people, No high availability or multi-instance reliability for production use, DevOps workflows require centralized logging, not CLI-based tools, Creates tech debt as a shortcut rather than proper observability solution

Feature requests: Graph log match counts over time by source node, API/daemon/UI instead of CLI-only interface, JSON output for piping to other tools, npm package for Node.js projects (npx qlog, JS import), Support for querying across multiple machines/clusters

Competitors

Other products that read as similar to this one — 64 launches clear the similarity bar, closest 8 shown.

Attention rank: #20 of 65 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 120 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a observability & eval tool for Media & entertainment yet.