Hugr is an Open Source Data Mesh Platform and high-performance GraphQL Backend.
Designed for seamless access to distributed data sources, advanced analytics, and geospatial processing — Hugr powers rapid backend development for applications and BI tools. It provides a unified GraphQL API across all your data.
Key Benefits
Data Mesh–Ready
Build federated, domain-driven schemas without losing visibility or control.
Modern Data Stack Support
Natively integrates with Postgres, DuckDB, Parquet, Iceberg, Delta Lake, and REST APIs.
Geospatial & Analytical Power
Perform spatial joins, aggregations, and OLAP queries — all in GraphQL.
Cluster-Ready & Extensible
Scale with your workloads or embed the engine directly in your Go services.
Secure by Design
Enforce fine-grained access policies with built-in authentication and role-based permissions.
Use Cases
1. Data Access Backend for Applications
hugr acts as a universal GraphQL layer over data sources:
- Rapid API deployment over existing databases and files
- Centralized schema and access control
- Unified interfaces for apps and BI tools
- Minimal manual integration
- Ideal for data-first applications
2. Embedding the Engine into Custom Services
hugr's core is a reusable Go package:
- Can be embedded into your own services
- Serves as a query compiler and execution engine
- Supports custom Go functions as data sources
- Unifies internal and external data in one schema
3. Building Data Mesh Platforms
hugr is perfect for Data Mesh architecture:
- Modular schema definitions
- Federated access through a single API
- Decentralized data ownership
- Domain-specific modeling and scaling
- Easy onboarding of teams and data sources
4. Analytics, DataOps and MLOps Integration
hugr enables:
- Support for OLAP and spatial analytics
- Export to Arrow IPC and Python (pandas/GeoDataFrame)
- Server-side jq transformations
- Caching and scalability for heavy workloads
- Integration of ETL/ELT and ML pipeline results
Powered by DuckDB
hugr leverages DuckDB - the blazing-fast in-process analytical database - as its core engine. This enables lightning-speed cross-source JOINs and aggregations directly in memory, combining data from PostgreSQL, S3 Parquet files, CSV, and geospatial formats in a single GraphQL query. With zero network latency and OLAP-optimized performance, DuckDB makes hugr the perfect choice for analytic workloads and data mesh architectures.