MQTT Sparkplug

A single source of truth for all industrial data, structured around the ISA-95 asset hierarchy. The UNS provides a decoupled, real-time data exchange layer between OT and IT systems. MQTT Sparkplug is the most common protocol for implementing a UNS because its topic namespace naturally maps to the physical asset hierarchy, enabling plug-and-play interoperability without custom code.

• Eliminates point-to-point integrations
• Provides a semantic structure for all data producers and consumers
• Enables self-discovery of new assets by any authorized subscriber

An international standard (IEC 62264) for integrating enterprise and control systems. It defines a hierarchical model of equipment, physical processes, and business functions across five levels, from the physical process (Level 0) to the enterprise (Level 4). MQTT Sparkplug's topic structure is explicitly designed to mirror the ISA-95 equipment hierarchy, making it the natural protocol for bridging the Level 2/3 OT world with the Level 4 IT world.

• Defines standard terminology for manufacturing operations
• Provides the canonical asset model that Sparkplug's namespace reflects
• Enables consistent data modeling across disparate vendor systems

An extension of the OPC UA standard that decouples data producers from consumers using a publish-subscribe pattern, often over MQTT or AMQP. While classic OPC UA uses a client-server model requiring direct connections, PubSub enables scalable cloud and edge integration. MQTT Sparkplug and OPC UA PubSub are complementary: Sparkplug defines the payload format and state management, while OPC UA provides a rich information modeling framework.

• Enables OPC UA data to be transported over MQTT brokers
• Supports both JSON and binary UADP message encoding
• Decouples the information model from the transport protocol

A specialized time-series database designed for industrial environments to archive high-fidelity process data over long periods. MQTT Sparkplug provides the stateful, typed data stream that historians consume. The Sparkplug Birth/Death certificate mechanism ensures the historian always knows the current state and metadata of every asset, even after a disconnection, enabling accurate historical analysis and regulatory compliance.

• Stores years of high-resolution sensor data for trend analysis
• Relies on Sparkplug's data typing for correct long-term storage
• Uses Birth certificates to auto-configure new tag storage

A centralized service that stores and manages the schemas for data formats like Avro or Protobuf. While MQTT Sparkplug uses Google Protocol Buffers as its native payload encoding, a schema registry ensures that all producers and consumers can reliably deserialize the structured data. This is critical in a polyglot environment where Java, Python, and C# applications all need to interpret the same Sparkplug messages without ambiguity.

• Manages versioned Protobuf schemas for Sparkplug payloads
• Ensures forward and backward compatibility during upgrades
• Centralizes governance of the data contract between OT and IT

A formal agreement between a data producer and its consumers that defines the schema, semantics, and quality guarantees of the data being exchanged. In an MQTT Sparkplug architecture, the combination of the topic namespace, the Protobuf schema, and the Birth/Death certificate mechanism constitutes a robust, machine-enforceable data contract. This ensures that a temperature sensor from Vendor A and a pressure transmitter from Vendor B publish data in a consistent, predictable format.

• Defines the structure, meaning, and reliability of each data point
• Prevents downstream consumer breakage when producers change
• Enables automated validation and quality monitoring at the broker level