An open-source toolkit for building a Unified Namespace to ingest, contextualize, and store factory data for Industrial IoT platforms.
United Manufacturing Hub is an open-source toolkit for building Industrial IoT platforms that ingest, contextualize, and store factory data. It enables manufacturers to create a Unified Namespace, centralizing production-line data for real-time monitoring, analytics, and digital transformation. The solution offers both a lightweight Docker-based edge gateway (UMH Core) and a full-stack Kubernetes deployment (UMH Classic) to suit different scalability needs.
Manufacturing engineers, industrial IoT developers, and IT teams in production environments who need to unify and analyze factory data from PLCs, sensors, and other devices. It's also suitable for organizations pursuing digital transformation initiatives in industrial settings.
Developers choose UMH for its open-source flexibility, dual deployment options (edge vs. full-stack), and focus on building a reliable Unified Namespace without vendor lock-in. Its ability to buffer data locally and integrate with cloud management provides resilience and ease of maintenance in industrial networks.
The data platform for manufacturing
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Centralizes all plant-floor data into a single logical namespace, enabling standardized access and correlation across machines and sites, as described in the Unified Namespace overview.
Offers both a lightweight Docker-based edge gateway (UMH Core) and a full-stack Kubernetes deployment (UMH Classic), allowing adaptation to different infrastructure needs from edge to cloud.
Includes Redpanda for local data buffering during network interruptions, ensuring data isn't lost in industrial environments with unstable connectivity, as highlighted in UMH Core features.
Provides a cloud-based console at management.umh.app for monitoring, configuration, and upgrades, simplifying maintenance of distributed UMH instances.
UMH Core instances require connection to the cloud-based management console for setup and monitoring, which may not suit air-gapped or high-security environments without offline alternatives.
UMH Classic deployment depends on Kubernetes infrastructure and Helm charts, adding operational overhead and expertise requirements compared to lighter-weight solutions.
Documentation is scattered across multiple sites (website, docs portal, learning portal), which can make it challenging to find cohesive, up-to-date guidance for advanced setups.
Setting up Data Flow Components and pipelines requires YAML configuration and understanding of Benthos-UMH, posing a steep learning curve for teams new to streaming data ingestion.