Relational databases are by far the most common type of database, and as software developers it’s safe to say that they are the kind of database most of us got started on, and probably still use on a regular basis. And one thing that they all have in common is the way they structure data. InfluxDB, however, structures data a little bit differently.

Today, many of the internet’s busiest websites and applications rely on NGINX to run smoothly. And many of those websites and apps are run as cloud-native services in Kubernetes. In particular, the NGINX Ingress Controller is a best-in-class traffic management solution for cloud‑native apps in Kubernetes and containerized environments that uses NGINX as a reverse proxy, load balancer, API gateway, cache, or web application firewall.

With Industry 4.0 fundamentally transforming manufacturing systems and processes through IIoT technologies, manufacturers large and small are seeking the most efficient ways to reap its benefits. Potential gains include optimizing operations, generating data-driven insight, creating new revenue streams, and accelerating innovation. To paint the big picture, let’s start with a definition of Industry 4.0, followed by an explanation of what adopting it involves.

InfluxData prides itself on its effort to prioritize developer happiness. This included providing developers with a variety of tools to interact with InfluxDB v2 OSS or InfluxDB Cloud, so they can pick the development style that works best for them. This article assumes you’re using the InfluxDB Cloud Free tier, which is the easiest way to get started and maintain InfluxDB. You can use any of the following tools for your IoT application development.

This article was written by Cameron Pavey, a full-stack dev living and working in Melbourne. Scroll below for this picture and bio. As a developer, it is likely that you will eventually run into a situation where a traditional relational database’s document stores don’t quite cut it. If you need to store points of data over time, you’ll likely need a time series database.

Aggregations are a powerful tool when processing large amounts of time series data. In fact, most of the time you’re going to care more about the min, max, mean, count or last values of your dataset than you will about the raw values you’re collecting. Knowing this, InfluxDB and the Flux language make it as easy as possible to run these aggregations, whenever and wherever you need to, and sometimes that leads people to running them in ways that aren’t as efficient as they could be.

If you’re building an IoT application on top of InfluxDB, you’ll probably use a graphing library to handle your visualization needs. Today we’re going to take a look at the charting library, Highcharts, to visualize our time series data with InfluxDB Cloud. However, I also encourage you to take a look at Giraffe, a React-based visualization library that powers the data visualizations in the InfluxDB 2.0 UI.

One of the best things about getting started with InfluxDB over traditional relational databases is the fact that you don’t need to pre-define your schema in order to write data. This means you can create a bucket and write data in seconds, which can be pretty powerful to developers who care way more about the application they’re building than the mechanics of storing the data.

This post was written by James Hickey. Scroll below for full bio and picture following this article. Time series databases (TSDBs) can transform the way you handle streams of data in real time or IoT applications. In this tutorial, you’ll learn how to set one up in a C# application. Relational databases have their place. They’re great at things like data normalization, avoiding duplication, indexing over specific data points (like columns), and handling atomic changes to the schema.