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Community | 2 Mar, 2023
Introducing Quix Streams, an open source library for telemetry data streaming
Lightweight, powerful, no JVM and no need for separate clusters of orchestrators. Here’s a look at our next-gen streaming library for C# and Python developers including feature summaries, code samples, and a sneak peek into our roadmap.
Tomas Neubauer
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Tomáš Neubauer, CTO & Co-Founder
ML predictions with Python and Apache Kafka
Tutorial | 8 Feb, 2023
Build a simple event-driven system to get ML predictions with Python and Apache Kafka
Use the Quix Streams Python library to continuously stream email records from a CSV file, get an ML inference for each record, then stream the results back to a new Kafka topic.
Tomas Neubauer
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Tomáš Neubauer, CTO & Co-Founder
Blog 181 feature
Explainer | 31 May, 2022
Edge, fog and cloud computing: Where you process data matters
Computing in the cloud, in the fog or at the farthest edge can make a significant difference in technical applications that are processing large volumes of data at high speeds
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Mike Rosam, CEO & Co-Founder
Blog 189 feature
Explainer | 23 May, 2022
How to build a no-code pipeline for sentiment analysis with our Snowflake connector
Three Quix connectors let you move data from Twitter to a Snowflake database while transforming it along the way. Learn how to set up the pipeline without writing any code.
Steve Rosam
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Steve Rosam, Full-stack developer
Blog 187 feature
Community | 17 May, 2022
Discover new tools you’ll actually enjoy using (really!)
Members of the streaming community share their favorite tools — from backend development to organizing workflows to developing website copy. We have suggestions that you’ll actually enjoy using.
Steve Rosam
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Steve Rosam, Full-stack developer
The Stream May 2022
Community | 10 May, 2022
The Stream — May 2022 edition
The May 2022 edition of The Stream: covering this month in stream processing on the internet.
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words by
Mike Rosam, CEO & Co-Founder
Blog 176 feature
Community | 6 May, 2022
The (surprisingly) long history of streaming real-time data
Streaming real-time data didn’t magically appear from nowhere. Its long history isn’t just fascinating — it’s full of familiar examples that your family can understand.
Kiersten Thamm
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Kiersten Thamm, Head of Technical Content
Blog 170 feature02
Community | 26 Apr, 2022
Data pipelines done right at the Kafka Summit 2022
Companies building the modern data stack gathered this week to discuss the challenges, shortcuts and benefits of stream processing. Here’s what you need to know.
Kiersten Thamm
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Kiersten Thamm, Head of Technical Content
Blog 163 feature
Strategy | 19 Apr, 2022
Three ways to increase the value you get from the data you already collect
Data’s value depends on how you use it. We’ll look at three ways to increase the value you get from the data you’re already collecting.
1611064394032
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Mike Rosam, CEO & Co-Founder
The Stream April 2022
Community | 13 Apr, 2022
The Stream — April 2022 edition
The April 2022 edition of The Stream: covering this month in stream processing on the internet.
1611064394032
words by
Mike Rosam, CEO & Co-Founder
Blog 162 feature
Strategy | 5 Apr, 2022
Dark data: how companies are capturing data and failing to use it
“Dark data” is the data being collected and stored without a plan for future use. It’s often dumped into data lakes with little to no thought for how it could actually be used in the future — that’s someone else’s problem.
1611064394032
words by
Mike Rosam, CEO & Co-Founder

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