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Graphic featuring Apache Kafka and ActiveMQ logos
Explainer

ActiveMQ vs. Kafka: A comparison of differences and use cases

The main difference between them is that Kafka is a distributed event streaming platform designed to ingest and process massive amounts of data, while ActiveMQ is a traditional message broker that supports multiple protocols and flexible messaging patterns.
Mike Rosam
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Mike Rosam
Graphic featuring Apache Kafka and RabbitMQ logos
Explainer

Apache Kafka vs. RabbitMQ: Comparing architectures, capabilities, and use cases

The main difference between them is that Kafka is an event streaming platform designed to ingest and process massive amounts of data, while RabbitMQ is a general-purpose message broker that supports flexible messaging patterns, multiple protocols, and complex routing.
Mike Rosam
Words by
Mike Rosam
Explainer

Apache Beam vs. Apache Spark: Big data processing solutions compared

The main difference between Spark and Beam is that the former enables you to both write and run data processing pipelines, while the latter allows you to write data processing pipelines, and then run them on various external execution environments (runners). But what are the other differences between Spark and Beam, and how are they similar?
Alex Diaconu
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Alex Diaconu
simplified diagram of a machine learning pipeline
Explainer

The anatomy of a machine learning pipeline

Explore the characteristics, challenges, and benefits of machine learning pipelines, and read about the steps involved in training and deploying ML models to production.
Alex Diaconu
Words by
Alex Diaconu
Graphic featuring Apache and Kafka logo.
Explainer

Kafka vs Pulsar: Streaming Data Platforms Compared

An in-depth comparison of Kafka and Pulsar, covering criteria such as architectural differences, operational attributes, developer experience, ecosystems, deployment options, and security.
Alex Diaconu
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Alex Diaconu
Three data processing icons in blue background.
Explainer

The fundamentals of real-time machine learning

What is real-time machine learning? How is it different from batch ML? What are common real-time ML use cases? What are the challenges of building real-time ML capabilities? All these questions and more are answered in this article.
Mike Rosam
Words by
Mike Rosam
Man standing in front of a labyrinth illustration.
Explainer

Real-Time infrastructure tooling for data scientists

Explore the evolution of new tools for real-time pipelines that aim to solve the ongoing problem of data scientists' need for more infrastructure expertise.
Tun Shwe
Words by
Tun Shwe
Language friction image timeline.
Explainer

Feature engineering has a language problem

Should data scientists know Java? Java and Scala underpin many real-time, ML-based applications—yet data scientists usually work in Python. Someone has to port the Python into Java or adapt it to use a Python wrapper. Neither of these options is ideal, so what are some better solutions?
Tun Shwe
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Tun Shwe
Orange and green chart on blue background.
Explainer

Time series analysis: a gentle introduction

Explore the fundamentals of time series analysis in this comprehensive article. Learn about key concepts, use cases, and types of time series analysis, and discover models, techniques, and methods to analyze time series data.
Javier Blanco
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Javier Blanco
Black chart on colorful background.
Explainer

Telemetry data explained

Gain a thorough understanding of telemetry data and how it works, learn about its benefits, challenges, and applications across different industries, and discover technologies you can use to operationalize telemetry.
Javier Blanco
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Javier Blanco
Text on black background saying unknown partition error.
Explainer

How to fix the unknown partition error in Kafka

A look at the most common causes of Kafka's "unknown topic or partition" error along with practical steps and solutions to help you fix it.
Peter Nagy
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Peter Nagy
Kafka vs Flink logo images.
Explainer

Apache Kafka vs Apache Flink: friends or rivals?

Explore the unique features and limitations of Apache Kafka and Apache Flink and learn how these open source streaming titans can either join forces or operate independently.
Tun Shwe
Words by
Tun Shwe
Illustration of two people in the desert.
Explainer

Bridging the gap between data scientists and engineers in machine learning workflows

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.
Mike Rosam
Words by
Mike Rosam
Animated rocket going down.
Explainer

The drawbacks of ksqlDB in machine learning workflows

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.
Mike Rosam
Words by
Mike Rosam
Quix vs Flink logos on purple background.
Explainer

Quix as an Apache Flink alternative: a side-by-side comparison

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.
Mike Rosam
Words by
Mike Rosam
Kinesis vs Kafka logos on orange background.
Explainer

Kinesis vs Kafka - A comparison of streaming data platforms

A detailed comparison of Apache Kafka and Amazon Kinesis that covers categories such as operational attributes, pricing model, and time to production while highlighting their key differences and use cases that they typically address.
Mike Rosam
Words by
Mike Rosam
Quix and AWS logos on grey background and a bike.
Explainer

Exploring real-time and batch analytics for e-bike telemetry with Quix and AWS

How Brompton's experiments with Quix and AWS technology are paving the way for an enhanced e-bike riding experience.
Mike Rosam
Words by
Mike Rosam
SQL CDC logo image.
Explainer

Build a CDC pipeline with the Quix SQL Server connector

Create a CDC pipeline and publish data to Kafka topics in just a few minutes with our open source SQL Server connector.
Steve Rosam
Words by
Steve Rosam
The stream

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