Database for IoT: storing and processing data from a large number of devices

It is essential that devices connected to each other via a network interact quickly and produce the desired results without human intervention. This is only possible with a high-quality infrastructure that can quickly process a large flow of information. An important element of this infrastructure is the IoT database, where data from all connected devices is collected, stored and analyzed. In this article, we will look at how an IoT database works and how to optimize its use.

What is a database for IoT devices

IoT, also known as the Internet of Things, IoT or “Internet of Things” is a network of connected devices and technologies that share data and interact with each other. A simple example is a fitness bracelet that collects information about your physical condition and sends it to your smartphone, where it is processed and analyzed.

Well-known examples of IoT also include:

• smart home - home appliances (smart TVs, refrigerators, lights, air conditioners) and security systems that can be controlled through apps;
• industrial IoT - sensors and systems for monitoring the condition of equipment in factories, tracking productivity and automation;
• smart cities - street lighting control systems, traffic monitoring.

All information received from such systems must be stored and processed somewhere. For this purpose, developers, including MEGASITE specialists, use IoT storages capable of instant processing, filtering and analyzing information.

Characteristics of IoT databases

To effectively fulfill their tasks, quality databases for IoT systems must meet the following requirements:

• have capacious storage capacity, as Big Data (large amounts of information) is expected to be handled;
• easily withstand the influx of information without loss of performance and delays;
• quickly distribute data to the right tiers;
• Work productively with IoT data that comes in multiple formats;
• track how the values of the right metric change over time to analyze trends and identify patterns, and correctly predict outcomes;
• guarantee high reliability, so that data is always available for analysis and is not lost in case of failures;
• visualize information in an understandable way (e.g., with a graph);
• integrate with different systems and applications;
• securely protect against hacking.

Flexibility in deployment makes data bases more versatile, allows their optimal use in different environments, as it improves performance, reliability and speed of information processing. This requires storage to be deployed in different locations - on the device itself, on a nearby server, in the cloud, in a data center.

Features of working with IoT data

How the database for IoT works depends on the type of storage - hot (streaming) or cold (static). The former focus on information that is constantly changing, while the latter focus on storing data that does not need constant adjustments. The choice depends on the customer's goals, but it is often necessary to apply both forms.

Separately, it is worth noting graph databases for IoT systems, which actively use AI algorithms to effectively model and store complex relationships between objects. Now this direction is considered to be very promising.

Hot IoT databases

Streaming databases for IoT are suitable for applications where real-time processing and storage of information is important. They provide fast access to frequently used and actively changing data.

The features of hot databases for IoT data include:

• high performance and processing speed;
• instantaneous results;
• minimal latency.

To work with actively changing data, NoSQL is often used. This is the name of heterogeneous storage management systems, which differ from traditional relational (SQL) systems by flexibility in structure and scalability.

Cold IoT databases

A static database for IoT operations is designed for archived data or infrequently needed information. Since constant updating of files is not required, the emphasis is on storing them safely and securely.

Unlike hot storages, they do not provide ultra-fast access. In terms of price, a cold database for IoT is less costly, as cheaper storage methods - such as HDDs (hard disk drives) or low-cost cloud solutions - are used.

Graph database for IoT functioning

This is the name given to a type of storage that is designed to store and process information coming from different devices. For this purpose, a graph model is used, where the following are involved:

• nodes - objects (devices, sensors) that generate data and users that receive this data;
• edges - links between objects when one device interacts with another (for example, a sensor sends information to a server).

Graph databases for IoT make heavy use of AI, which makes it easy to handle complex, multi-level relationships, including unstructured, rapidly changing information. The graph model effectively keeps track of all dependencies. This is useful, for example, when analyzing supply chains or sensor and device interactions in smart homes, as well as for rapid fraud detection.

How to optimize the processing and storage of data from IoT devices

For a database for IoT to be efficient, it is very important to optimize its performance. For this purpose, different methods and technologies are used, among which it is worth highlighting:

• decentralization, when filtering and analysis of information are performed as close as possible to the source of their origin, rather than on remote central servers. A special algorithm determines whether local processing is sufficient or whether the data needs to be transferred further;
• refusal of a continuous flow of information to the server in favor of batch transmission in order to reduce the load on it. This way of working with IoT data is especially useful when using devices that have limited resources;
• high-quality compression (archiving) helps save traffic, storage space, speeds up data transfer, and reduces the risk of data loss;
• use of AI to optimize work with files. For example, the system itself determines what information should be sent to an archive or cold database. AI can automatically delete information that has no business value;
• scaling, which allows new servers, nodes, and technologies to be connected to the database;
• breaking down large volumes of information into smaller, manageable pieces (shards). Each of these parts is stored on different servers or nodes, which allows the database to process large amounts of information more efficiently and increases its scalability.

To learn more about IoT database development for your project, contact the manager of IT company MEGASITE. We are engaged in website development and offer comprehensive solutions for effective storage management for IoT devices.

To contact us, call +38 (050) 3986 274 or leave your contacts in the feedback form on our website.