Athar is a self-hosted, high-performance Telemetry & Push Notification Engine built for absolute scalability and sub-ms ingestion latency. It's a production-grade open-source alternative to expensive third-party services, giving you 100% control over data and privacy. Built with an event-driven architecture: NestJS, Kafka (event buffer), ClickHouse (OLAP DB for fast aggregations), and Redis/BullMQ. Spin it up with one command: `docker compose up` 🐋
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Hey Product Hunt community! 👋
I'm Abdallah Yassein, the creator of Athar.
As software engineers, we've all been there: you build a great product, it starts to scale, and suddenly your third-party telemetry, tracking, and notification bills skyrocket. Charging per event or tracked user forces many startup teams to make hard compromises on data retention and user privacy just to stay within budget.
I built Athar to fix this. I wanted a production-grade, 100% self-hosted engine that gives engineering teams absolute control over their infrastructure, scaling data, and privacy without the premium price tag.
To achieve sub-millisecond ingestion latency and make sure the system absorbs sudden, massive traffic spikes seamlessly, I went with an event-driven architecture:
🚀 The Architecture Stack:
• NestJS: Powering stateless ingestion mesh nodes and independent background workers.
• Apache Kafka (KRaft): Acting as a high-throughput distributed streaming buffer to absorb peak loads.
• ClickHouse: A powerful columnar OLAP database optimized for lightning-fast aggregation queries on billions of rows.
• Redis & BullMQ: Handling fast API key validation, L1/L2 caching, and robust queue management.
🐋 Zero Infra Headaches:
You don't need a complex dev-ops setup to test it. I’ve bundled the entire production-ready stack into a single unified configuration. Just clone the repo and run: `docker compose up`.
Athar is fully open-source under the MIT License. I'm incredibly excited to share it with you all today and would love to hear your thoughts, system design feedback, or any feature requests you have.
If you like what I've built, please support the project with an Upvote here and a 🌟 Star on GitHub!
Thank you so much! 🙏🚀