The Quix blog

A monthly round-up of the most interesting news coming out of the stream processing ecosystem

Moving code from prototype to production can be tricky—especially for data scientists. There are many challenges in deploying code that needs to calculate features for ML models in real-time. I look at potential solutions to ease the friction.

Using ksqlDB for real-time feature transformations isn't as easy as it looks. I revisit the strategy to democratize stream processing and examine what's still missing.

A monthly round-up of the most interesting news coming out of the stream processing ecosystem

Learn how to reprocess a stream of data with the Quix Streams Python library and Apache Kafka. You'll ingest some GPS telemetry data into a topic and replay the stream to try out different distance calculation methods.

Explore the differences between Quix and Apache Flink and find out when it's better to use Quix as a Flink alternative. If you’re searching for Apache Flink alternatives, this guide offers a detailed, fair comparison to help you make an informed decision.

A comparison of Apache Kafka & Amazon Kinesis covering operational attributes, pricing and time to production, highlighting their key differences and use cases

A monthly round-up of the most interesting news coming out of the stream processing ecosystem

How Brompton's experiments with Quix and AWS technology are paving the way for an enhanced e-bike riding experience.

Learn why data compression is vital and how use it with Kafka and kafka-python, focussing on gzip—one of the strongest compression tools that Kafka supports.

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.

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.

How can you send time-series data to Apache Kafka using Python and Pandas? Plus Apache Flink news, memes, and meetups

Use Python to process time series data and send it to Apache Kafka. You'll use a large sample data set from an online-retailer and send the records in batches with Pandas and the kafka-python library.

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

How to build a powerful currency alerting pipeline in a few minutes with Quix and CoinAPI.

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

Why we've partnered with MMC Ventures, Project A Ventures and Passion Capital to accelerate our growth.

Create a CDC pipeline and publish data to Kafka topics in just a few minutes with our open source SQL Server connector.

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

As the internet of things evolves, so does its application in industrial settings. Find out how to take Industrial IoT from a helpful tool to transformative technology with streaming data integrations.

How CloudNC makes better predictions for maintenance, generates insights with very low latency, and transforms its factory operations with streaming data.

If your last IoT project wasn’t wholly successful or you’d like to progress along the learning curve faster, we’ve got you covered.