Being aware of the various open-source IoT frameworks available will help businesses to choose the best based on their requirements.
The most basic IoT architecture consists of various components like sensors and data acquisition systems, edge analytics, and data centers. These components require secure network ecosystems to facilitate data transmission among them. IoT frameworks help developers to create these ecosystems that can help create a stable first mile of IoT. They act as the bridge between sensors, actuators, and cloud servers to enable secure communication using network protocols. Businesses can select between two different types of IoT frameworks: commercial and open-source. Commercial IoT frameworks can be as costly as $1,000 per month. And they usually come with limited API support, libraries, and innovations. Such limitations of commercial IoT frameworks have encouraged the use of open-source frameworks. Every open-source framework comes with its own features and advantages over the others. Hence, choosing the best framework based on their needs can be challenging for businesses. To choose among the most suitable frameworks, businesses should be aware of their scalability, reliability, customization, protocols, hardware support, and cloud technology. And to help businesses be aware of these factors, here is a list of some most commonly used open-source IoT frameworks.
Some open-source IoT frameworks are best for scalability, some other for customization, and a few others for security and easy integration. Having the right information about the most commonly used open-source IoT frameworks will help businesses to choose the ideal framework for them.
Kaa is one of the most widely used open-source IoT frameworks. It is a framework majorly based on Java libraries and released under the Apache 2.0 license. Apache provides a copy of its license for every derivative work. And this license is provided only if developers are able to provide unequivocal statements proving that the source code has been modified. Apache also disclaims that if a case of patent infringement is filed against any developer, then the license granted to that developer will discontinue from the date the litigation is filled.
Since Kaa is licensed under the Apache 2.0, and imposes strict rules on redistribution rights, which increases reliability. Kaa provides real-time end-device monitoring and multi-tenant integration for enhancing scalability. The Kaa platform’s protocol is built on MQTT (a lightweight IoT protocol), but it can support any IoT protocol. It allows users to choose between encrypted and unencrypted channels for communication. Kaa open-source IoT framework is already used to deploy several IoT solutions for industries ranging from retail to healthcare.
Zetta is an API-first IoT platform, popularly used to develop scalable solutions. API-first in the sense that it can convert any device into an API for easy integration and connectivity. This increases its ability to scale. Zetta is based on Node.js programming language libraries and released under MIT license. MIT is the simplest and most permissive license. It basically allows developers to use source codes according to their preferences. The license also has a disclaimer saying that copyright holders will not be held responsible for any derivative work. Thus, the MIT license allows the greatest customization to developers. And this makes Zetta one of the most customizable open-source IoT frameworks.
Converting every device into an API helps Zetta servers to run everywhere, be it on the cloud, PCs, or single-board computers. Zetta’s architecture is optimized for data-intensive tasks so that developers and businesses can scale the solutions according to their needs, and gain valuable insights from the collected data.
Similar to Kaa, DeviceHive is released under Apache 2.0 license, making it a reliable and secure option for creating IoT solutions. But, what makes it different from Kaa is its multilingual library support. DeviceHive supports libraries of various programming languages like Java, Node.js, Python, Android, and iOS. This makes it a more customizable, scalable, and device-agnostic. IoT solutions developed with the help of DeviceHive can be easily integrated with other device clouds through secure mesh protocols. For instance, developers can easily integrate their IoT solutions with Alexa or visualization dashboards. DeviceHive enables quick foundations of analytics using some of the world’s best big data solutions like ElasticSearch, Apache Spark, Cassandra, and Kafka. This makes it one of the most preferred frameworks for building IoT solutions for processing big data. DeviceHive can provide IoT solutions for several industries, including automotive, healthcare, travel, retail, and many more. DeviceHive development is supported by IoT professionals from DataArt who have developed many IoT solutions like a smart thermostat, voice-controlled smart environments for hotels, and climate monitoring system using DeviceHive framework.
SiteWhere is a Java library supported open-source IoT framework. But it can run multiple programming languages other than Java, such as Node.js and Python. It is released under the CPAL 1.0 license. CPAL chart for Common Public Attribution License is an extended version of Mozilla Public License. CPAL, as the name suggests, requires attribution to the original developer in the case of any derivative work. SiteWhere supports a multi-tenant microservice infrastructure, where every task from acquiring data to processing it and storing it on the cloud is distributed as microservices. This microservice-based infrastructure makes SiteWhere scalable. SiteWhere provides deploy anywhere, scale everything feature. It allows on-premises or almost every cloud provider deployment. It also offers pre-developed middleware solutions to eliminate the need for custom development.
Distributed Services Architecture (DAS) is a multilingual library-based IoT framework. It facilitates development for what can be called the most secure IoT solutions. Firstly it is released under the Apache 2.0 license that makes it reliable. And on top of that, it enables communication among devices in a decentralized manner. DSA framework has three core components, DSBroker, DSLink, and nodeAPI. DSLinks wrap up a certain amount of domain-specific DSA library. This piece of the library is then exposed as an entity on the network that allows protocol translation and data stream acquisition. The ability of DSLinks to wrap up a purpose-specific library makes DSA highly customizable. DSBrokers act as routers for transmission of data streams acquired by DSLinks. DSBrokers can connect with each other to form a scalable and distributed network. The nodeAPI enables protocol transmission for secure communication among DSBrokers. The library of DSA stored in DSLinks is an ever-growing repository. Every developer and solution provider can contribute to some of the most popular programming languages like Java, Dart, and Python to enlarge it. This multilingual support for the DSA library enables it' easy integration into devices.
Open-source frameworks are cost-effective. But only if you choose the right framework based on your needs. Selecting the wrong framework can cost more than commercial ones. Hence, selecting the right framework is the key, and knowing the features of various frameworks will help you choose the best. But, if you are not sure of what you want, then open-source IoT frameworks are preferable. With the cost-effective deployment, they become the best choice for initial testing and deployment. And once you are clear about what you want to achieve, then you can easily decide between going for open-source frameworks or commercial ones.
Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.