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December 21, 2022
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Industry insights

The Stream — December 2022 edition

The December 2022 edition of The Stream: covering this month in stream processing on the internet.

The Stream December 2022 banner.

Python stream processing, simplified

Pure Python. No JVM. No wrappers. No cross-language debugging. Use streaming DataFrames and the whole Python ecosystem to build stream processing applications.

Python stream processing, simplified

Pure Python. No JVM. No wrappers. No cross-language debugging. Use streaming DataFrames and the whole Python ecosystem to build stream processing applications.

Data integration, simplified

Ingest, pre-process and load high volumes of data into any database, lake or warehouse, without overloading your systems or budgets.

The 4 Pillars of a Successful AI Strategy

Foundational strategies that leading companies use to overcome common obstacles and achieve sustained AI success.
Get the guide

Guide to the Event-Driven, Event Streaming Stack

Practical insights into event-driven technologies for developers and software architects.
Get the guide
Quix is a performant, general-purpose processing framework for streaming data. Build real-time AI applications and analytics systems in fewer lines of code using DataFrames with stateful operators and run it anywhere Python is installed.
Image showing icons of Quix CoinAPI.

How to deploy a currency alerting pipeline with Quix and CoinAPI

There's some painful heavy lifting required to build a currency alerting pipeline. Using Quix and CoinAPI means you can avoid most of it. Our CTO Tomas Neubauer has put together a tutorial to show you how you can build a reliable app so you can check prices, compare against others and trigger external actions based on meeting thresholds.

Read the tutorial

Web page of car listing.

Real-time personalisation of search results with Auto Trader's customer data platform

How Auto Trader improved the search experience with Kafka, Snowplow, and GCP.

Read more

Scheme showing how Quicksilver works.

Quicksilver: near real time platform at Myntra

Myntra created a (near) real-time data processing platform around Apache Kafka and Apache Spark, using Redis as a feature store for ML. The article is a nice reference architecture for real-time data platforms.

Read more

Illustration with why Kafka text on it.

Apache Kafka and Python

Last year Francesco Tisiot delivered a great explainer on Apache Kafka and Python. Francesco provides some sage advice on adding Kafka using Python libraries.

Watch on YouTube

Three men wearing Christmas clothes.

Happy Quix-mas from the Quix team!

The winner of this year's best (worst) Christmas outfit competition in the Quix team was too hard to pick. So Matt Lyver (Lead visual designer), Quique Ruis (SRE) and Patrick Mira Pedrol (Head of Software) take joint honours. Jump into our Slack community, The Stream, and share a picture of your best festive attire – bonus points for any data-related puns! ☃️

More insights and news

  • The three best-performing articles we shared this year:
  • Understanding streams in Redis and Kafka - Read more
  • Streaming-first infrastructure for real-time machine learning - Read more
  • Evolution of streaming pipelines in Lyft's marketplace - Read more
  • You can apply to become a speaker at Kafka Summit London here

What’s a Rich Text element?

The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.

Static and dynamic content editing

A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!

How to customize formatting for each rich text

Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.

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