Bringing the power of the Internet of Things to the manufacturing industry, IIoT projects are getting more and more attention. There is a lot of hype around the industrial IoT and for a reason: it has the potential to completely revolutionize the industry, allowing de-centralized operations in factory floors, to increase efficiency and safety, and to reduce labor costs considerably. However, the truth is that to effectively adopt IIoT practices is being problematic for many manufacturers.
Fair enough, the IIoT implies serious challenges. Apart from the cultural and corporate shifts, the data requirements are severe: volumes are higher than ever, real-time responses are needed, and every industry comes with its own particular set of tools, characteristics, and problematics.
Nonetheless, to successfully implement IIoT practices is not as intimidating as it might seem. Sure, to change paradigms is never easy—but a big part of the problem is simply a lack of clarity about the real needs of the IIoT. When the right strategies are implemented and the optimal technologies are used, the execution of IIoT projects becomes easier and more accessible.
Choosing the right database for IIoT applications: what to look for?
Let’s take the database as an example. Databases are not a one-for-all solution: every use case comes with a specific set of priorities, and the IIoT is not an exception. Understanding these priorities is the first step in order to find a database that fits. IIoT applications are a use case on their own: they come with a combination of requirements that differentiate them from other IoT cases.
- First of all, industrial projects not only imply the processing of huge amounts of data: the IIoT workload comes with high data variety as well. This is a differentiating factor with other IoT use cases, which may imply very high volumes but a reduced number of data types.
- Secondly, the database must be prepared to provide millisecond responses even under highly concurrent loads. Parallel usage is a given in IIoT applications, and the database performance must be reliable even when it is queried by multiple users.
- It is also important that the database remains flexible, being able to adapt to existing tools and the changing needs of the industry.
- Lastly, in a sector that relies on low economic margins, it is mandatory to use efficient solutions to avoid unnecessarily high database costs once the industry grows.
New problems… Old solutions?
All these points are important for the success of IIoT. However, when it’s time to pick the right database, manufacturers discover that the most popular database solutions don’t quite fit the needs of the IIoT use case.
For example, traditional relational databases provide numerous advantages, but they cannot handle the volume and complexity of Industrial IoT applications. NoSQL databases improve scalability and performance, but they come with high costs and a high level of complexity in terms of management and integration. And time-series specialized databases are inadequate to handle IIoT projects by themselves, since their performance significantly degrades with intense parallel usage and they are not prepared to optimally handle the unstructured data that is part of the industrial machine data workload.
So... How do we make it work?
The short answer is this: by using technologies specialized in IIoT.
CrateDB is a database built for the modern industry. It is designed to offer what the use case really needs: simple scalability, real-time performance even with complex queries, easy accessibility and integration, and high cost-efficiency.
If you are interested in a longer, more insightful answer, this webinar will answer all your questions. It is hosted by Christian Lutz, the CEO of Crate.io, and covers this topic in detail. Christian addresses the importance of adopting IIoT practices for the future of the manufacturing industry, presenting how to effectively bring IIoT projects to success. Learn directly from an IIoT expert!