Top Free & Open-Source IIoT Platforms for Smart Manufacturing

Industrial Internet of Things (IIoT) platforms connect machines, sensors, and enterprise systems — enabling real-time visibility, analytics, and automation across the factory floor. As manufacturers move toward Industry 4.0, open-source IIoT frameworks have become essential for companies seeking flexibility, transparency, and control over their industrial data without vendor lock-in.

1. ThingsBoard

Best for: full-stack industrial IoT deployments with dashboards and device management.
ThingsBoard offers data collection, processing, visualization, and remote control for connected devices. It supports MQTT, CoAP, and HTTP, and integrates with edge nodes or cloud instances. Role-based access, alarms, and rule engine make it enterprise-ready.
License: Apache 2.0 / Open Source.
Used by: automotive parts and energy OEMs for smart factory dashboards and energy monitoring.

2. EdgeX Foundry

Best for: edge-layer data processing and protocol translation.
A Linux Foundation project, EdgeX Foundry provides a microservices architecture for connecting sensors, PLCs, and applications. It bridges OT and IT systems, supporting Modbus, OPC-UA, REST, and MQTT. Highly modular and compatible with containerized deployments.
License: Apache 2.0 / Open Source.
Used by: Dell, Accenture, and industrial integrators for factory edge deployments.

3. Mainflux

Best for: secure and scalable IIoT backends.
Mainflux is a modern, open-source, cloud-native IIoT platform written in Go. It supports multiple protocols (MQTT, WebSocket, CoAP, HTTP) and integrates with Grafana, InfluxDB, and Node-RED.
License: Apache 2.0 / Open Source.
Used by: system integrators building connected manufacturing networks.

4. Fledge (LF Edge Project)

Best for: industrial edge computing and predictive maintenance.
Fledge is an edge computing platform for data ingestion, filtering, and ML inference at the edge. It connects to SCADA and PLC systems while pushing curated data upstream to cloud or MES.
License: Apache 2.0 / Open Source.
Used by: oil, energy, and automotive firms for condition monitoring and edge analytics.

5. OpenRemote

Best for: industrial and smart energy control platforms.
OpenRemote enables building management, factory control, and IoT visualization. It supports MQTT, Modbus, HTTP, BACnet, and KNX. Comes with flexible dashboards, rule automation, and geolocation-based logic.
License: AGPLv3 / Open Source.
Used by: European smart factories and utilities for integrated operations monitoring.

6. Kura (Eclipse IoT Project)

Best for: gateway management and field connectivity.
Eclipse Kura provides a Java/OSGi-based framework for managing IoT gateways, devices, and local data processing. It acts as the connectivity layer for edge devices before data is sent to cloud or MES.
License: Eclipse Public License / Open Source.
Used by: OEMs using Eurotech hardware and Eclipse-based industrial stacks.

7. Node-RED

Best for: flow-based industrial logic and integration.
Originally developed by IBM, Node-RED provides an intuitive drag-and-drop interface for connecting data flows between machines, APIs, and databases. Supports MQTT, OPC-UA, HTTP, and Modbus. Frequently used for SCADA-lite setups or rapid integration pilots.
License: Apache 2.0 / Open Source.
Used by: integrators and automation engineers for quick IIoT prototypes and data routing.

8. ChirpStack (formerly LoRa Server)

Best for: LoRaWAN-based industrial IoT networks.
ChirpStack provides a full LoRaWAN network server stack for connecting wireless sensors in industrial or remote sites. Integrates with ThingsBoard and Grafana for dashboards and analytics.
License: MIT / Open Source.
Used by: logistics, energy, and environmental monitoring companies.

9. Kaa IoT Platform

Best for: cloud and hybrid industrial IoT deployments.
Kaa offers device management, data collection, analytics, and digital twin visualization. It supports multiple deployment models (on-prem, cloud, hybrid) and integrates with Kafka, InfluxDB, and Grafana.
License: Apache 2.0 / Open Source.
Used by: industrial OEMs and solution providers across Europe and Asia.

10. OpenIoT

Best for: research and interoperability projects.
OpenIoT provides a middleware framework for connecting and querying IoT devices via semantic web technologies. It’s used mostly for research or university-driven IIoT projects focusing on interoperability.
License: Apache 2.0 / Open Source.
Used by: R&D institutions and pilot smart factory programs.

Comparison Table

Recommendations

For production-grade deployments, ThingsBoard, EdgeX Foundry, and Mainflux stand out — all offering enterprise-level scalability and community maturity. Fledge adds strong predictive maintenance capabilities at the edge.

For integrators and automation engineers, Node-RED and Kura provide quick connectivity and easy prototyping. OpenRemote is ideal for bridging energy, building, and production systems under one control platform.

For wireless and distributed environments, ChirpStack delivers robust LoRaWAN integration, especially useful for remote asset monitoring.

IIoT in 2025 is defined by openness, modularity, and data sovereignty. Manufacturers no longer rely on closed ecosystems — they build hybrid architectures where open-source IIoT platforms handle data acquisition, processing, and visualization seamlessly across edge and cloud. Choosing the right platform isn’t about features alone — it’s about alignment with your production strategy, integration stack, and ability to evolve without licensing constraints.

About MDCplus

Our key features are real-time machine monitoring for swift issue resolution, power consumption tracking to promote sustainability, computerized maintenance management to reduce downtime, and vibration diagnostics for predictive maintenance. MDCplus's solutions are tailored for diverse industries, including aerospace, automotive, precision machining, and heavy industry. By delivering actionable insights and fostering seamless integration, we empower manufacturers to boost Overall Equipment Effectiveness (OEE), reduce operational costs, and achieve sustainable growth along with future planning.