On-demand resources

Learn how to build pipelines in Quix with natural language and find out how we build an MCP server from API docs.

Reliable industrial data ingestion needs a system that can handle volume, integrity, instability, variety, latency, and silos.

In this webinar, our customer CloudNC presents how they optimize manufacturing processes in their factory with Quix.

In this webinar, we go through real world examples from industrial companies in the energy, manufacturing and transport sectors.

In this webinar, we discuss some of the challenges around ingesting high volumes of high frequency sensor data into a centralized cloud data store.

🧑‍🏫 This third episode in the course expands on stateful transformations from the last episode with an industrial use case: downsampling. You’ll learn about time series data, the challenges when dealing with high velocity data and why downsampling is often required. You’ll be introduced to InfluxDB (a time series database) and work through solving common challenges in a coding session.

🧑‍🏫 This second episode in the course covers the basics of stateful transformations. You’ll learn the concepts, understand why state is useful, why it’s often required and lastly get to grips with stateful operations in a coding session.

This first episode in the course is an introduction to stream processing. You’ll learn some fundamental concepts and will have an understanding of why and when to use stream processing. There will be a practical section showing you how to get started with producing, consuming and transforming data.

Learn how to leverage a Quix project template to sync data from InfluxDB 2.x to InfluxDB 3.x.

Tun Shwe, VP of Data at Quix, is discussing the challenges of real-time stream processing with Redis and how Quix aims to solve them

Our VP of Data, Tun Shwe, is joined by Anais Dotis from InfluxDB to discuss real-time predictive maintenance in this live webinar.

Explore best practices for crafting a scalable time series data pipeline with OpenTelemetry, Quix, and InfluxDB.

We explore the methodology for crafting a scalable time series data pipeline, leveraging Quix and InfluxDB.

Discover how you can become proactive by using Quix and InfluxDB together.

Python is one of the easiest languages to do Kafka stream processing with. In this video we'll take you through it step-by-step, from an empty directory to a workhorse example of Kafka-Streams style message transformations.

Getting data out of Apache Kafka is easy if you know how, so let's go through an example step-by-step. In this walkthrough we take you through the process of creating a simple Kafka Consumer using the Quix Streams library.

Getting data into Apache Kafka is easy if you know how, so let's go through an example step-by-step. In this walkthrough we take you through the process of creating a simple Kafka Producer using the Quix Streams library.

Looking to boost your AI initiatives but facing setbacks in deployment, data quality, or team alignment? This guide reveals foundational strategies that leading companies use to overcome these common obstacles and achieve sustained AI success.

Transitioning to an event-driven architecture but unsure about your tech stack? In this guide, we walk you through the most popular EDA messaging patterns and technologies so that you can choose the right tools for the job.

Find out why analysts and market-watchers agree that traditional data processing must be replaced by stream processing.