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orionbelt-semantic-layer
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orionbelt-semantic-layer

Active·★ 101·NOASSERTION·Updated 2026-10-22

OrionBelt Semantic Layer is an open-source Semantic Sidecar that injects governed business semantics into AI and analytics systems without architectural changes. It allows users to define dimensions, measures, and business rules in YAML, which are then compiled into optimized, dialect-specific SQL for various databases.

#Semantic Layer#SQL Generation#Data Governance#Agentic AI#Data Analytics#Multi-Dialect SQL
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Guides
#API
#YAML Modeling
$ Install
$ pip install orionbelt-semantic-layer
↗ Visit site★ GitHub
01

Features

01YAML-based Semantic Modeling (OBML)
02AST-based, Multi-dialect SQL Compilation
03Diverse Integration Surfaces (REST, MCP, Gradio, pgwire, Flight SQL)
04Advanced Agent-Facing API for AI Integration
05Source-level Freshness-Driven Result Cache
02

Compatibility

Python
Runtime
Verified via docs
Docker
Containerization
Verified via docs
BigQuery
Database
Verified via docs
ClickHouse
Database
Verified via docs
Databricks
Database
Verified via docs
Dremio
Database
Verified via docs
03

Quick start

1
$ pip install orionbelt-semantic-layer
04

Use cases

↳Governed Data Access for AI Agents
↳Building and Powering Analytics Workflows
↳Defining and Monitoring Data Quality Checks
↳Calculating Regulatory and Business KPIs
↳Simplifying Reporting Use Cases
05

Alternatives

⚡Top VS:
VSdst★16→VSmnemiq★81→VSOnCo★237→

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On this page
01Features02Compatibility03Quick start04Use cases05Alternatives
VS
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See all alternatives →
ralforion /
orionbelt-semantic-layer
↗

Open-source Semantic Sidecar for AI, analytics, and governed data systems. Compiles declarative YAML models into optimized SQL, semantic context, KPIs, and DQ rules.

101
Last commit1d ago
StatusActive
CategoryRAG / Knowledge Base
Links
Documentation↗Discussion↗Issues↗Releases↗
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