The TypeScript Semantic Layer for ClickHouse
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I've built a type-safe semantic layer in code, for ClickHouse. If you're building analytics off ClickHouse in TypeScript, I would love your feedback.With hypequery there is no platform to adopt, no YAML sprawl. It runs where your app runs.Key features:- Define metrics once, reuse them everywhere: Declare dimensions and measures in one place and then pull from the same source of truth.- Compiles to ClickHouse SQL: No service, no proxy, no extra runtime to deploy. It's a library that generates SQL and runs where your app runs.- Multi-tenancy & Authentication ready: Cross-tenant queries are blocked at the query layer, helpers to plug into your existing auth.- Agent-native: A dataset is a declared set of dimensions and measures, so it doubles as an allowlist. Includes an MCP server to hand an LLM a typed catalog to query.- Runtime HTTP entry point: serve() exposes any dataset as an endpoint, so the same type-safe definitions back your dashboards and your API.
HN · launched Jun 27, 2026 · 8 upvotes (top 50%) · 0 views
Niche: semantic search and rag tools · 93 launches, 0 in the last 7 days · Explore this niche →
Category and tags
- Horizontal
- Analytics & BI
- Developer
- Not AI
- Commercial product
Visit website ↗ Source listing ↗
More like this: all 93 launches in semantic search and rag tools →
Could you build this?
Partial While basic SQL query generation in TypeScript is straightforward, creating a robust, type-safe semantic layer compiler for complex ClickHouse queries requires advanced compiler and AST design.
What it would actually take: Building a type-safe semantic layer requires designing a domain-specific TypeScript DSL using advanced conditional typing and template literal types for compile-time safety. The engine needs an internal relational query planner/compiler that transforms dimensional metrics into highly optimized, dialect-specific ClickHouse SQL (handling subqueries, rollups, aggregations, and ClickHouse-specific join constraints). Production reliability requires deep database systems engineering and extensive test suites against running ClickHouse clusters.
Discussion
6 comments analyzed.
Concerns raised: Production readiness - young library in critical read path, Team trust and adoption in production systems, Governance gaps, Relationship-aware queries not yet fully implemented, BI/GraphQL connectivity limited
Feature requests: Contract snapshots/diffs for version control, Richer metrics and time semantics, BI and GraphQL connectivity, Better generated tooling
Competitors
Other products that read as similar to this one : 116 launches clear the similarity bar, closest 8 shown.
Attention rank: #66 of 117 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 235 days after the earliest competitor.
- Chkit · hn · 2026-10-12 · 9 upvotes · similarity 0.53
- 0Sql · hn · 2026-10-06 · 7 upvotes · similarity 0.53
- Managed Postgres with native ClickHouse integration · hn · 2026-01-22 · 45 upvotes · similarity 0.49
- Typebase · hn · 2026-08-26 · 119 upvotes · similarity 0.46
- SLayer, a semantic layer maintained by your agent · hn · 2026-05-11 · 12 upvotes · similarity 0.46
- Strata · hn · 2026-09-30 · 24 upvotes · similarity 0.46
- SensorFlow · ph · 2026-09-27 · 1 upvotes · similarity 0.45
- TypeGraph · hn · 2026-02-24 · 5 upvotes · similarity 0.44
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