Combine the ClickHouse database with streaming data from Kafka, RedPanda, and Photon, for a powerhouse of real-time and historical data.

This text provides a detailed examination of two specific windowing implementations in event stream processing: hopping and tumbling windows.

Learn how Apache Doris breaks down data silos for insurance firms, streamlining customer data integration and boosting efficiency.

Apache Kafka simplifies data discovery and dynamic data integration by providing a unified platform for event streaming and data integration.

Top papers on distributed systems; distributed system papers every software engineer should read.

Discover WarpStream, a powerful and user-friendly Kafka API-compatible data streaming platform designed to simplify your data infrastructure.

Java's ongoing evolution ensures its place as a top programming language in 2024, offering robust performance, scalability, and extensive community support.

In this article, you'll better understand all the components associated with Apache Kafka and how they work together.

Learn Kafka Schema Evolution: Understand, Manage & Scale Data Streams with Confluent Schema Registry. Essential for Data Engineers & Architects.

Discover how Apache Kafka’s data retention and querying capabilities make it similar to a database and learn when to use Kafka for database-like use cases.

This is a study comparing environments for Apache Kafka. The ultimate goal is to find the most effective setup and achieve the best price-performance ratio.

7/13/2024: Top 5 stories on the HackerNoon homepage!

Explore the First In First Out (FIFO) mechanism in message brokers and learn how to maintain message order across different systems.

Learn how to integrate the Apache Kafka component into your .Net Aspire project using Visual Studio 2022.

Article explaining the importance of speedy data analytics and implementation of robust data infrastructure to achieve the same with live streaming data.

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Thanks to Tom de Ruijter, [https://medium.co

Unbounded data refers to continuous streams of data generated from sources that require real-time or near-real-time processing for timely insights.

Streaming systems are capable of producing correct, consistent, and repeatable results.

This article explores different caching strategies—such as in-memory, distributed, and hybrid approaches—for optimizing performance in microservices or monolith