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C# Date Classes: Types, Formats, and How to Use Them

In this article, we will be exploring C# date classes and how to leverage them to handle and manipulate date data in our applications. We will see the different types of date objects that C# handles and the formats that can be represented, and we will learn how to cleanly process date information from users. Let’s jump right in.

A Guide to Working with the Dateutil Module in Python

Python is a highly versatile language. From software engineering to machine learning and data analysis, it’s everywhere. As a multipurpose scripting and programming language, it’s often utilized for manipulating and working with data. So, when you’re working with Python, whether you’re analyzing data or writing scripts, you’re likely to encounter dates and time stamps.

Don't Let Time Series Data Break Your Relational Database

This article was originally published in The New Stack and is reposted here with permission. It’s tempting to stuff time series data into the familiar Postgres or MySQL database, but that’s a bad idea for many reasons. To the uninitiated or unfamiliar, time series data exhibits similar characteristics to relational data, but the two data types have some critical differences.

Querying InfluxDB Cloud with the Java Flight SQL Client

InfluxDB Cloud 3.0 is a versatile time series database built on top of the Apache ecosystem. You can query InfluxDB Cloud with the Apache Arrow Flight SQL interface, which provides SQL support for working with time series data. In this tutorial, we will walk through the process of querying InfluxDB Cloud with Flight SQL, using Java. The Java Flight SQL Client is part of Apache Arrow Flight, a framework for building high-performance data services.

InfluxDB 3.0 vs ADX

Over the past few years, time series is one of the fastest growing database categories in the world. As more and more organizations realize how critical time series data is to their operations, more database options entered the market. InfluxDB has been the leading time series database for years, and with the release of InfluxDB 3.0, it remains at the vanguard of the time series world.

6 Project Ideas to Get Started with IoT

A look at the main things you need to consider when planning your IoT project with links to tutorials and source code. There’s a lot of stuff written about the Internet of Things (IoT) at a conceptual level that doesn’t really cover anything concrete. If you’ve ever wanted to get started on a real IoT project but didn’t know where to start, you are in the right place.

Metrics, Logs and Traces: More Similar Than They Appear?

This article was originally published in The New Stack and is reposted here with permission. They require different approaches for storage and querying, making it a challenge to use a single solution. But InfluxDB is working to consolidate them into one. Time series data has unique characteristics that distinguish it from other types of data. But even within the scope of time series data, there are different types of data that require different workloads.

OpenTelemetry Tutorial: Collect Traces, Logs & Metrics with InfluxDB 3.0, Jaeger & Grafana

Here at InfluxData, we recently announced InfluxDB 3.0, which expands the number of use cases that are feasible with InfluxDB. One of the primary benefits of the new storage engine that powers InfluxDB 3.0 is its ability to store traces, metrics, events, and logs in a single database. Each of these types of time series data has unique workloads, which leaves some unanswered questions. For example: Luckily this is where our work within OpenTelemetry comes into play.

Backfill Missing Time Series With SQL

Time series data streams are often noisy and irregular. But it doesn’t matter if the cause of the irregularity is a network error, jittery sensor, or power outage – advanced analytical tools, machine learning, and artificial intelligence models require their data inputs to include data sets with fixed time intervals. This makes the process of filling in all missing rows and values a necessary part of the data cleaning and basic analysis process.

Best Practices to Build IoT Analytics | InfluxData

This article was originally published in The New Stack and is reposted here with permission. Selecting the tools that best fit your IoT data and workloads at the outset will make your job easier and faster in the long run. Today, Internet of Things (IoT) data or sensor data is all around us. Industry analysts project the number of connected devices worldwide to be a total of 30.9 billion units by 2025, up from 12.7 billion units in 2021.