DeviceHive
UnclaimedAn open-source IoT data platform for seamless device connectivity, data processing, and analytics.
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TL;DR - DeviceHive
- Open-source IoT data platform for device connectivity and management.
- Scalable deployment options using Docker and Kubernetes for various cloud environments.
- Integrates with big data analytics tools for real-time and batch processing.
Pricing: Free forever
Best for: Individuals & startups
Pros & Cons
Pros
- Highly flexible and scalable deployment options
- Supports a wide range of device connectivity protocols and client libraries
- Strong integration capabilities with leading big data and analytics tools
- Open-source nature provides transparency and customization opportunities
- Commercially supported for enterprise-grade deployments
Cons
- Requires technical expertise for deployment and management
- Reliance on external big data solutions for full analytics capabilities
Key Features
Open-source under Apache 2.0 licenseContainer-based service-oriented architectureKubernetes orchestration for scalability and availabilityREST API, WebSockets, and MQTT for device connectivityDevice-agnostic with client libraries for various programming languages (including Android, iOS, ESP8266)Plugin service for integration with other device clouds and platforms (e.g., Alexa)Custom JavaScript code execution for behavior customizationIntegration with ElasticSearch, Apache Spark, Cassandra, and Kafka for analytics
Pricing
Free
DeviceHive is completely free to use with no hidden costs.
About DeviceHive
By Toolradar Team·
DeviceHive is an open-source IoT data platform designed to simplify the development and management of Internet of Things solutions. It provides a robust foundation for connecting various devices, processing their data, and integrating with other platforms. The platform is built with scalability in mind, supporting deployments from single virtual machines to enterprise-grade clusters using Docker Compose and Kubernetes, making it suitable for both startups and established enterprises.
DeviceHive enables connectivity for any device through REST API, WebSockets, and MQTT, offering client libraries for multiple programming languages, including Android and iOS. It facilitates easy integration with other device clouds, visualization dashboards, and services like Alexa, allowing for custom behavior through JavaScript code. The platform also provides a strong base for analytics by leveraging big data solutions such as ElasticSearch, Apache Spark, Cassandra, and Kafka for real-time and batch processing, including machine learning capabilities.
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DeviceHive FAQ
What specific deployment options does DeviceHive offer for scaling from prototyping to enterprise solutions?
DeviceHive supports deployment using Docker Compose and Kubernetes, allowing for private, public, or hybrid cloud environments. It can scale from a single virtual machine for prototyping to an enterprise-grade cluster, leveraging Kubernetes for highly granular scalability and availability to handle growing production volumes.
How does DeviceHive ensure device-agnostic connectivity, and what types of devices can it connect?
DeviceHive ensures device-agnostic connectivity by supporting REST API, WebSockets, and MQTT protocols. It provides client libraries for various programming languages, including Android and iOS, and can even connect low-end Wi-Fi enabled devices like ESP8266.
Can DeviceHive integrate with existing visualization dashboards or smart home assistants like Alexa?
Yes, DeviceHive can directly integrate with visualization dashboards of your choice and smart home assistants like Alexa. This is achieved through its supported protocols and the plugin service feature, which also allows for customizing DeviceHive behavior with JavaScript code.
What big data solutions does DeviceHive leverage for analytics and machine learning on device data?
DeviceHive provides the foundation to build analytics by leveraging world-class big data solutions such as ElasticSearch, Apache Spark, Cassandra, and Kafka. It specifically includes Apache Spark and Spark Streaming support for running batch analytics and machine learning directly on device data.
What kind of commercial support is available for DeviceHive, given its open-source nature?
DeviceHive is commercially supported by DataArt's Internet of Things practice. This provides professional consultants and engineers who can assist with implementation, customization, and ongoing maintenance for enterprise users.
Source: devicehive.com