WaveHouse
Supabase for ClickHouse
Details
- External ID
- 49377989
- Source
- HN
- Company
- —
- Product
- WaveHouse
- Website domain
- wavehouse.dev
- Launched
- Aug. 20, 2026
- Cohort
- —
- Upvotes
- 20
- Upvotes percentile
- 0.7452956989247311
- Tags
- —
- Fetched at
- Sept. 10, 2026, 5:32 a.m.
- Updated at
- Sept. 10, 2026, 5:32 a.m.
Description
While building an IoT telemetry solution, we ran into hurdles with Clickhouse. For one, you can't insert quickly AND durably into Clickhouse without setting up something like Kafka, which gets complicated for quick projects wanting to make use of Clickhouse's powerful features. Then, trying to actually query Clickhouse and show data in a UI required a whole backend API to handle auth and permissions.We figured that all these parts together – fast, durable ingest, row-level and column-level security and roles, and realtime streaming – were a lot of scaffolding to have to rebuild for every project we wanted to use Clickhouse in. So, we built them all into a single Go binary to be deployed alongside Clickhouse, to help lower Clickhouse's barrier to entry. We call it WaveHouse.Would love any feedback as we work on improving and adding more features to this OSS project!
Enrichment
- Theme
- Vertical
- Horizontal
- Function
- Data infrastructure
- Audience
- Developer
- AI stance
- Not AI
- Project type
- Commercial product
- Normalized one-liner
- backend for clickhouse
- Manually corrected
- False
Could you build this?
Partial An API proxy with basic routing to ClickHouse is straightforward to vibe code, but implementing reliable high-throughput micro-batching, memory-efficient queuing, backpressure, and real-time streaming requires nuanced systems engineering.
What it would actually take: Built with Go and TypeScript, utilizing high-throughput networking frameworks (e.g., fasthttp or native Go net/http). The difficult components are the asynchronous buffer engine with write-ahead-logging (WAL) or durable memory buffering to prevent data loss during spikes, schema validation against ClickHouse types, and tiered caching with automatic invalidation. Requires deep knowledge of ClickHouse's internal batching mechanics, HTTP streaming, and distributed memory management.
Discussion
4 comments analyzed.
Competitors
Other products that read as similar to this one — 17 launches clear the similarity bar, closest 8 shown.
Attention rank: #4 of 18 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 281 days after the earliest competitor.
- ObsessionDB · hn · 2026-01-23 · 12 upvotes · similarity 0.49
- Managed Postgres with native ClickHouse integration · hn · 2026-01-22 · 45 upvotes · similarity 0.43
- The TypeScript Semantic Layer for ClickHouse · hn · 2026-06-27 · 8 upvotes · similarity 0.42
- CH-UI v2 · hn · 2026-02-20 · 9 upvotes · similarity 0.42
- Logchef · hn · 2025-12-22 · 5 upvotes · similarity 0.40
- SensorFlow · ph · 2026-09-27 · 1 upvotes · similarity 0.39
- StreamHouse · hn · 2026-02-25 · 10 upvotes · similarity 0.39
- 500k+ events/sec transformations for ClickHouse ingestion · hn · 2026-04-08 · 13 upvotes · similarity 0.38
Other launches for this product
- No other launches for this product.
Same idea, different domain
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