June 16, 2022
Industry insights

The Stream — June 2022 edition

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

The Stream June 2022 banner.
Quix Streams combines an Apache Kafka client with a stream processing library, offering a feature-rich pure Python alternative to the kafka-python library. Deploy on your stack or on Quix Cloud for scalable, stateful and fault-tolerant ETL without the headache of cross-language debugging.

👉 Star the repo on GitHub and pip install quixstreams to get started.

The potential of stream processing never ceases to amaze me.

We’ve already written about how stream processing enables extensive personalization of commercial products and lets businesses get the most up-to-date information to the people who need it most. In an effort to improve the lives of individuals and societies, teams have employed stream processing to increase the effectiveness of donations, help doctors deliver tailored healthcare, make cities safer and match people to the resources they need. The Quix team has even demonstrated that stream processing makes machines more human.

But that’s just the beginning. I’ve recently learned more about the application of stream processing to time-series data in national security and disaster prevention. Michael Debouver, a cloud architect at Airbus, recently explained how his team built a streaming architecture that ingests, moves and makes sense of satellite data during an environmental catastrophe. The system doesn’t even involve the internet, and it doesn’t lag for even two seconds. That way emergency services know how to direct people to safety and create accurate rescue plans. Other researchers are discovering connections between armed conflicts and climate change through time-series data and machine learning. Who knows what’s coming next?

Empowering products and people to immediately respond to data can save lives. I’m honored that Quix offers one piece of the puzzle to make that possible.

Four topographic world maps.

Can time-series data help researchers understand the relationship between armed conflicts and climate change? Yes.

Find out how by reading “Modelling armed conflict risk under climate change with machine learning and time-series data.”

Learn more

Big data London banner.

We’re gathering at Big Data London — get your tickets now!

If you’re in London September 21-22, come meet other stream enthusiasts at Quix’s booth at Big Data London.

Join us →

Software engineering daily text.

Decodable Streaming with Eric Sammer

Decodable Founder @esammer recently sat down with the @software_daily podcast to talk about stream processing and its role in modern data platforms.

Give it a listen →

Purple banner of a streaming meeting between two people.

To stream, or not to stream? A conversation about when to use (and how we built) stream processing systems

Watch two Quix founders discuss stream processing at McLaren F1 and pick up some helpful information about data processing along the way.

Check it out →

More insights

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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