3 posts tagged with "mqtt"

Photo by Jan Antonin Kolar on Unsplash

Since joining ReductStore's project, I've been exploring alternative solutions to get a better understanding about how the project fits into current echosystem.

To give you some context, we will look at solutions to store data from IoT devices (e.g. sensors, cameras, etc.) that commonly use MQTT to communicate with each other.

MQTT stands for Message Queuing Telemetry Transport and is a lightweight messaging protocol designed to be efficient, reliable, and scalable, making it ideal for collecting and transmitting data from sensors in real time.

Why is this important when choosing a database?

Well, MQTT is format-agnostic, but it works in a specific way. We should therefore be aware of its architecture, how it works, and its limitations to make the right choice. This is what this article is about, we will try to cut through the fog and explore some key factors to consider when selecting the right option.

Let's get started!

The MQTT protocol is a simple way to connect different sources of data to applications, which makes it very popular for IoT (Internet of Things) applications. Some MQTT brokers can save messages for a while, even when the MQTT client is offline. However, sometimes, you need to keep this data for a longer time. In those cases, it's a good idea to use a time series database.

There are many time series databases available, but if you need to store a history of images, sensor data, or Protobuf messages, you might want to use ReductStore. This database is designed to store a lot of blob data and works well with IoT and edge computing.

ReductStore has client SDKs (Software Development Kits) for many programming languages. This means you can easily use it in your existing system. In this example, we'll be using the Python SDK from ReductStore.

Now, let's make a simple MQTT application to see how this all works.

The MQTT protocol is widely used in IoT applications because of its simplicity and ability to connect different data sources to applications using a publish/subscribe model. While many MQTT brokers support persistent sessions and can store message history as long as an MQTT client is not available, there may be cases where data needs to be stored for a longer period. In such cases, it is recommended to use a time series database. There are many options available, but if you need to store unstructured data such as images, sensor data, or Protobuf messages, consider using ReductStore. It is a time series database specifically designed for storing large amounts of blob data and optimized for IoT and edge computing.

ReductStore provides client SDKs for many programming languages to integrate it into your infrastructure. In this example, we will use the client SDK for JavaScript.

Let's make a simple application to understand how to keep a history of MQTT messages using ReductStore and Node.js.