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Open-source event streaming platform built on S3. Kafka-compatible APIs, built-in SQL engine, schema registry — one Rust binary replaces Kafka + ZooKeeper + KSQL. Retention costs pennies, not thousands

64 starsRust

StreamHouse – Open-source Kafka alternative

Name: StreamHouse – Open-source Kafka alternative
Availability: InStock
Author: gbram

by gbram·Mar 11, 2026·3 points·0 comments

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AI Analysis

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S3-native storage slashes Kafka costs from thousands to $23 per TB monthly.

Strengths

•Single Rust binary replaces entire Kafka broker fleet with ZooKeeper complexity
•Kafka protocol compatibility means existing clients work without code changes
•Per-write durability modes let you trade latency for cost per workload

Weaknesses

•Author admits no battle-tested production deployments yet — risky for critical systems
•S3 read latency may not suit sub-millisecond streaming requirements

Post Description

Hey HN,

I built StreamHouse, an open-source streaming platform that replaces Kafka's broker-managed storage with direct S3 writes. The goal: same semantics, fraction of the cost.

How it works: Producers batch and compress records, a stateless server manages partition routing and metadata (SQLite for dev, PostgreSQL for prod), and segments land directly in S3. Consumers read from S3 with a local segment cache. No broker disks to manage, no replication factor to tune — S3 gives you 11 nines of durability out of the box.

What's there today: - Producer API with batching, LZ4 compression, and offset tracking (62K records/sec) - Consumer API with consumer groups, auto-commit, and multi-partition fanout (30K+ records/sec) - Kafka-compatible protocol (works with existing Kafka clients) - REST API, gRPC API, CLI, and a web UI - Docker Compose setup for trying it locally in 5 minutes

What's not there yet: - Battle-tested production deployments (I'm the only user so far) - Connectors for consumers to immediately connect to (i.e clickhouse, elastic search etc)

The cost model is what motivated this. Kafka's storage costs scale with replication factor × retention × volume. With S3 at $0.023/GB/month, storing a TB of events costs ~$23/month instead of hundreds on broker EBS volumes.

Written in Rust, 15 crates thus far. Apache 2.0 licensed.

GitHub: https://github.com/gbram1/streamhouse How it works blog on my main website: https://streamhouse.app/how-it-works

Happy to answer questions about the architecture, tradeoffs, or what I learned building this.