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Unified API for Your Data, Wherever It Lives

One GraphQL layer for all your data.

Access databases, files, and APIs through a single, secure interface — with domain ownership and centralized governance built-in.

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The hugr Data Mesh platform and GraphQL backend

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.

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Key Benefits

Data Mesh–Ready

Data Mesh–Ready

Build federated, domain-driven schemas without losing visibility or control.

Geospatial & Analytical Power

Geospatial & Analytical Power

Perform spatial joins, aggregations, and OLAP queries — all in GraphQL.

Modern Data Stack Support

Modern Data Stack Support

Natively integrates with Postgres, DuckDB, Parquet, Iceberg, Delta Lake, and REST APIs.

Cluster-Ready & Extensible

Cluster-Ready & Extensible

Scale with your workloads or embed the engine directly in your Go services.

Talk-to-data

Talk-to-data

Comming soon! Leverage natural language queries to access and analyze your data effortlessly.

Secure by Design

Secure by Design

Enforce fine-grained access policies with built-in authentication and role-based permissions.

Understanding Data Mesh

Data Mesh is a modern approach where teams own and publish their data as a product — just like they do with APIs or microservices.

Hugr enables this by giving every domain a flexible, secure, and unified way to expose their data using GraphQL.

Data Mesh visualization

Use Cases

Data Access Backend for Applications

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
Data Mesh Platform Architecture

2. 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
Analytics and MLOps Integration

3. 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
Vibe analytics

4. Vibe/Agentic Analytics

hugr MCP powers Vibe's analytics platform by:

  • Modular schema design for diverse data sources
  • Summarize data objects and their fields, relationships, functions, modules and data sources descriptions using LLMs to better understand business context
  • Lazy Hugr schema introspection tools to automatically generate GraphQL queries based on user requests
  • Allow models to build complex queries over multiple data sources and performs chain of queries to fetch and aggregate data as needed
  • Allow models to build JQ transformations to process and filter data server-side before returning results to users
DuckDB Logo

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.