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InfluxData

InfluxData Announces New Platform Enhancements at InfluxDays 2022

SAN FRANCISCO, November 2, 2022 – Today, InfluxData, creator of the leading time series platform InfluxDB, announced significant product enhancements at InfluxDays 2022, its annual developer and community event. New features including InfluxDB Script Editor, Telegraf Custom Builder, and Flux 1.0 support developers working with time series data, allowing them to do more with less code.

More Capabilities, Less Code: Announcing Platform New Features at InfluxDays 2022

The InfluxDB platform has evolved a lot over the past decade. But with every innovation we’ve added to the platform, the focus behind our efforts has remained the same: Build cool stuff for people who build cool stuff. What we mean by this is we want to make it incredibly easy for users to build valuable applications with their time series data. We do that by offering a wide range of tools, features, and resources that meet builders on their terms.

October Monthly Product Update - InfluxDB New Engine and More!

We love to write and ship code to help developers bring their ideas and projects to life. That’s why we’re constantly working on improving our product in sync with developer needs to ensure their happiness and accelerate Time To Awesome. This month is very special. We now have a new engine that significantly increases the “horsepower and torque” for InfluxDB.

Faster MQTT Data Collection with InfluxDB

Native MQTT eliminates the need to write custom code, orchestrate additional technology layers or incorporate additional hosting services. MQTT is a powerhouse within the Internet of Things (IoT) space. Its pub/sub model and lack of defined payload structure make it infinitely adaptable to the needs of modern sensors, devices and systems. IoT data is also time-series data.

Getting Started with Python and Geo-Temporal Analysis

This article was originally published in The New Stack and is reposted here with permission. Working with geo-temporal data can be difficult. In addition to the challenges often associated with time-series analysis, like large volumes of data that you want real-time access to, working with latitude and longitude often involves trigonometry because you have to account for the curvature of the Earth. That’s computationally expensive. It can drive costs up and slow down programs.

Welcome to InfluxDB IOx: InfluxData's New Storage Engine

Two years ago I announced that InfluxData was working on a new core for InfluxDB, a project we named InfluxDB IOx. InfluxDB IOx is a cloud-native, real-time, columnar database optimized for time series data built in Rust on top of Apache Arrow and DataFusion. Today I’m excited to announce that we deployed our next-generation storage engine that’s built on InfluxDB IOx in our InfluxDB Cloud platform.

Import CSV Data into InfluxDB Using the Influx CLI and Python and Java Client Libraries

With billions of devices and applications producing time series data every nanosecond, InfluxDB is the leading way to store and analyze this data. With the enormous variety of data sources, InfluxDB provides multiple ways for users to get data into InfluxDB. One of the most common data formats of this data is CSV, comma-separated values. This blog post demonstrates how to take CSV data, translate it into line protocol, and send it to InfluxDB using the InfluxDB CLI and InfluxDB Client libraries.