How to Select the Right IoT Database Architecture?

In the era of the Internet of Things (IoT), data is a valuable resource that powers innovation and business growth. But to harness the full potential of IoT data organizations need the right database architecture.

With a multitude of options available, choosing the best IoT database architecture can be a daunting task. However, technologists can simplify the process by evaluating the different types of IoT database architectures, such as static vs. streaming and SQL vs. NoSQL, to determine the best fit for their project.

In this article, we will discuss more about revolutionizing IoT applications with right database architecture. Let’s start!

Ultimate Guide to Choose an IoT Database

If you're building an IoT setup, you know that a reliable database is essential for success. But what exactly should you be looking for in a database that can handle the unique demands of IoT?

We have got you covered with our ultimate guide to choosing an IoT database.

Requirements for Edge Servers: Fast Writes and Analytics

Picture this: your IoT setup has multiple sensors streaming data to an edge server. Suddenly, one sensor's data gets caught in latency for 20 seconds, creating a pileup of data. To avoid losing any information, edge servers need to support extremely fast write operations. Look for a database with a high ingest rate that can handle bursts of data in real time. But it is not just about writes. Edge servers also need fast reads and analytics tools to make real-time decisions.

Requirements for Cloud Data Centers: Transform, Analyze, and Visualize

Once your data reaches the cloud, you need a database that can handle analysis and computations. Make sure the database has built-in analysis commands to avoid overhead in managing multiple tools. Downsampling and a retention policy are also critical for quickly querying historical data. Downsampling keeps high-precision data for a short time and less precise data for longer, informing trends and seasonality. A retention policy ensures that data is automatically deleted after a certain period, freeing up space for new information. Finally, you will need a visualization engine to display your IoT system's state and the ability to publish and subscribe.

Do not let your IoT setup fail because of an inadequate database. Choose one that meets the unique demands of IoT, from edge servers to cloud data centers.

4 Steps to Select the Perfect Database Platform for Your IoT Solutions

As the IoT industry rapidly expands, choosing the right database platform(s) can be an overwhelming task. With IoT solutions distributed across vast geographical regions, the traditional cloud-based approach is no longer sufficient. The need for a combination of fog computing at the edge and cloud computing has given rise to the demand for flexible database platforms that can process data at the edge and sync with the cloud.

But wait, there is more! Depending on your unique IoT use cases, the capabilities you want in your database could range from real-time data streaming to near-zero latency read operations, and everything in between.

Below are the four crucial steps to selecting the perfect database platform for your IoT solutions. Get ready to crack the code and unleash the full potential of your IoT systems!

Step 1: Specify Your Data Requirements

IoT solutions rely on the collection and processing of data from connected devices. Before you start building your solution, it’s important to identify your data needs.

Ask yourself −

• What decision-making and data processing tasks are assigned to the edge servers?

• Is the cloud solution installed in a single location or are they spread across several?

• What is the volume of data transferred between devices, edge servers, and the central server? What is the estimate for peak volume?

• Does the IoT solution have control over the actuators or devices & are real-time responses necessary?

• What business insights can you derive from the historical data?

Step 2: Your solution should be divided into separate software services

Once you have identified your data needs, it’s time to break down your solution into independent software services. It will help you design software components that perform specific tasks.

Here are some examples −

• Data Ingest − Collect and store logs and messages from devices

• Edge Analytics − Perform real-time decision-making at the edge

• Device Manager − Communicate messages to the devices

• System-wide Analytics − Collect data from edge servers and perform analytics operations

• Business Intelligence − Run reports, queries, and inferences from historical data

• IoT Data Stream Outlet − Normalize data to a common format and push them to subscribers

Step 3: Group Your Services Based on Client Data Requirements and Choose the Proper Databases

The next step is to group your services by their data needs and select the right databases. Hot databases are deployed close to the IoT devices to minimize network latency, while cold databases store historical data.

Here are some things to consider −

• Hot Database − In-memory databases are a good choice for hot databases. Look for flexibility with data formats, querying capabilities, messaging and queueing, a tiered memory model, high availability and disaster recovery, geo-distribution, and binary safe features.

• Cold Database − Historical data may grow to multiple terabytes, so storage solutions on commodity hardware are popular. Indexing data in a search engine for pattern matching and data aggregation can also be helpful.

Step 4: Evaluate Cost and Resource Efficiency

Classifying databases as hot or cold helps you narrow down your database choices. One high-speed database can meet the needs for the hot database in the majority of IoT use cases. Options for the cold database may range from relational databases to data lakes. Be mindful of creating a polyglot architecture with a mix of databases, as it can create unnecessary operational overhead.

With these four steps, you will be on your way to building an effective IoT solution that can handle the enormous amounts of data generated by connected devices.

Conclusion

Data is king in the IoT era, but only if it's managed with the appropriate database design. Although picking the ideal architecture can be challenging, you can completely transform your IoT database by taking the correct steps. From edge servers to cloud data centres, databases must be able to transform, analyse, and visualize data in real time across all of these platforms. With hot and cold databases, IoT solutions can be divided into independent software services to group data based on client requirements. In a world that demands flexibility, cost efficiency & resourcefulness an effective IoT solution relies on the perfect database platform.