The TypeScript Semantic Layer for ClickHouse
Details
- External ID
- 48696675
- Source
- HN
- Company
- —
- Product
- The TypeScript Semantic Layer for ClickHouse
- Website domain
- github.com
- Launched
- June 27, 2026
- Cohort
- —
- Upvotes
- 8
- Upvotes percentile
- 0.4952185792349727
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:26 p.m.
- Updated at
- Sept. 7, 2026, 9:26 p.m.
Description
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.
Enrichment
- Theme
- database infrastructure and developer tools
- Vertical
- Horizontal
- Function
- Dev tools
- Audience
- Developer
- AI stance
- Not AI
- Project type
- Commercial product
- Normalized one-liner
- typescript semantic layer for clickhouse
- Manually corrected
- False
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 — 66 launches clear the similarity bar, closest 8 shown.
Attention rank: #41 of 67 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 235 days after the earliest competitor.
- Managed Postgres with native ClickHouse integration · hn · 2026-01-22 · 45 upvotes · similarity 0.49
- Typebase · hn · 2026-08-26 · 119 upvotes · similarity 0.45
- SLayer, a semantic layer maintained by your agent · hn · 2026-05-11 · 12 upvotes · similarity 0.44
- SensorFlow · ph · 2026-09-27 · 1 upvotes · similarity 0.44
- TypeGraph · hn · 2026-02-24 · 5 upvotes · similarity 0.43
- Pg-typesafe · hn · 2026-02-17 · 69 upvotes · similarity 0.43
- WaveHouse · hn · 2026-08-20 · 20 upvotes · similarity 0.42
- SQLBraid · ph · 2026-09-18 · 1 upvotes · similarity 0.41
Other launches for this product
- No other launches for this product.
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