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IoT: Opt for the Right Open Source Database

Open Source For You

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July 2023

By harnessing the right open source database solutions for IoT, organisations can drive innovation, enhance data management, and get actionable insights that propel them ahead in the IoT landscape. Unlock the full potential of IoT by selecting the right set of open source databases.

- Dr Gopala Krishna Behara

IoT: Opt for the Right Open Source Database

The technology ecosystem of Internet of Things (IoT) is complex, and includes hardware, connectivity, platforms, middleware, analytics, operating systems, applications, and services.

As per IDC, there will be 41.6 billion connected IoT devices or 'things', generating 79.4 zettabytes (ZB) of data in 2025. Sixty-four per cent of those surveyed think open source is significant in deploying IoT, as per the IDC Global IoT DecisionMaker Survey. According to a survey by W3.Org, 91% of IoT developers use open source software, open hardware, or open data in at least one part of their development stack.

According to Statista, the total installed base of Internet of Things (IoT) connected devices is projected to amount to 75.44 billion worldwide by 2025. By 2030, IoT could enable US$ 5.5 trillion to $12.6 trillion in value globally, including the value captured by consumers and customers of IoT products and services, as per McKinsey.

With billions of devices generating trillions of bytes of data, it is very crucial for enterprises to organise, store and work with all the data that is generated.

In general, IoT applications leverage both relational and non-relational (NoSQL) databases. The selection of the type of the database depends on the application type. In most of the cases, a combination of both the databases can be utilised.

Most IoT applications are heterogeneous and domain-centric. Choosing the most efficient database for these applications can be challenging. The important parameters for choosing the right database for IoT applications are scalability, availability, ability to handle huge amounts of data, high processing speed, schema flexibility, integration with varied analytical tools, security and costs.

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