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November 30, 2022
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Industry insights

The Stream — November 2022 edition

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

The Stream November 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.
Quix Zoom team photo.

Quix raises $12.9m Series A to accelerate event-driven data apps

MMC Ventures have led our Series A round to help us bring streaming to more software organisations! We're looking for new Quixers to join us across our engineering and product to help us in our mission. Check out our careers page if you're interested in joining 🚀

Read our funding announcement

Explanatory scheme of Kafka and Flink.

Uber Freight Near-Real-Time Analytics Architecture

How Uber changed their analytics architecture to save $1.5 million in 2021 through improved performance.

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Increasing blue graph and decreasing red graph.

Real-Time at Pinterest

How Pinterest leverages real-time user actions in recommendations to boost home feed engagement volume

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Two people on a virtual meeting.

Shifting Data Science workloads from batch to streaming

Ralph Debusmann shares their journey of migrating from a batch machine learning platform to a real-time event streaming system with Apache Kafka® and delves into their approach to making the transition frictionless. The conversation is hosted by Streaming Audio's affable host Kris Jenkins.

Watch on YouTube

More insights and news

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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