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Jan 27, 2026 · Backend Development

7 Essential Kafka Design Patterns Every Engineer Should Master

This guide presents seven practical Kafka design patterns—single‑key single‑write, log compaction, multi‑consumer‑group fan‑out, retry and dead‑letter topics, exactly‑once processing with Streams, schema evolution with Avro, and choreography vs orchestration—detailing when to use each, core principles, code examples, tips, common pitfalls, and final recommendations for building reliable, observable, and maintainable event‑driven systems.

Design PatternsEvent StreamingKafka

0 likes · 9 min read

7 Essential Kafka Design Patterns Every Engineer Should Master

DevOps Coach

Dec 15, 2025 · Databases

Why PostgreSQL Is Becoming the Backend OS: From Search to Event Streaming

The article explains how PostgreSQL has evolved from a simple relational store into a versatile platform that supports full‑text search, vector similarity, geospatial queries, JSONB, message queues, and analytical workloads, allowing developers to replace multiple specialized tools with a single unified system.

Database ExtensionsEvent StreamingFull‑Text Search

0 likes · 6 min read

Why PostgreSQL Is Becoming the Backend OS: From Search to Event Streaming

Full-Stack Internet Architecture

May 27, 2025 · Big Data

Understanding Event Streaming in Kafka: Core Concepts, Architecture, and Use Cases

This article explains Kafka's event streaming concept, detailing events and streams, core components such as producers, topics, partitions, consumers, persistence, and typical real‑time data pipeline, event‑driven architecture, stream processing, and log aggregation use cases, highlighting its role as a foundational big‑data infrastructure.

Event StreamingKafkaReal-time Processing

0 likes · 7 min read

Understanding Event Streaming in Kafka: Core Concepts, Architecture, and Use Cases

Ma Wei Says

Mar 28, 2025 · Backend Development

Choosing the Right Message Queue: Kafka vs RocketMQ vs RabbitMQ Explained

This article compares Kafka, RocketMQ, and RabbitMQ, detailing their architectures, performance characteristics, strengths, and ideal use‑cases to help engineers select the most suitable message‑queue solution for high‑throughput, fault‑tolerant, and real‑time processing scenarios.

Distributed SystemsEvent StreamingHigh Throughput

0 likes · 11 min read

Choosing the Right Message Queue: Kafka vs RocketMQ vs RabbitMQ Explained

Bilibili Tech

Oct 11, 2024 · Big Data

Business Observability and Real-Time Event Streaming Architecture for Content Production

The paper proposes a business‑observability framework for a content‑production pipeline—illustrated by Bilibili’s workflow—by modeling archives as entities, assigning global AIDs for end‑to‑end tracing, and leveraging a Kafka‑Flink‑ClickHouse event‑streaming platform to monitor real‑time latency, bottlenecks, and safety audits across the entire production line.

Content ProductionEvent StreamingReal-time analytics

0 likes · 19 min read

Business Observability and Real-Time Event Streaming Architecture for Content Production

Rare Earth Juejin Tech Community

Apr 6, 2024 · Big Data

Deep Dive into Kafka’s Underlying Mechanisms: Sequential Writes, Sparse Indexing, Segment Storage, and Replication

This article explores Apache Kafka’s core storage architecture, explaining how sequential append‑only writes, sparse indexing, segmented log files, and a leader‑based replication mechanism together enable high‑throughput, reliable, and scalable event streaming for massive data workloads.

Big DataEvent StreamingKafka

0 likes · 11 min read

Deep Dive into Kafka’s Underlying Mechanisms: Sequential Writes, Sparse Indexing, Segment Storage, and Replication

Java Architect Essentials

Dec 7, 2021 · Big Data

Apache Kafka 3.0 Release Highlights and New Features

The article provides a comprehensive overview of Apache Kafka 3.0, detailing its core APIs, two main use‑cases, major feature additions, deprecations, KRaft consensus improvements, enhanced producer guarantees, and numerous KIP‑driven changes across the broker, client, Connect, Streams, and MirrorMaker components.

Apache KafkaEvent StreamingKIP

0 likes · 14 min read

Apache Kafka 3.0 Release Highlights and New Features

Architects Research Society

Oct 22, 2019 · Big Data

Continuous Delivery of Event Streaming Pipelines with Spring Cloud Data Flow

This article explains how to build, deploy, and continuously update event streaming pipelines using Spring Cloud Data Flow and Apache Kafka, covering common topologies, named destinations, parallel and partitioned streams, function composition, multiple input/output bindings, and practical shell commands for registration and management.

Continuous DeploymentEvent StreamingKafka

0 likes · 19 min read

Continuous Delivery of Event Streaming Pipelines with Spring Cloud Data Flow

Architects Research Society

Oct 20, 2019 · Big Data

Spring Cloud Data Flow: Building and Deploying Event Stream Pipelines with Apache Kafka (Part 3)

This article explains how Spring Cloud Data Flow, together with Spring Cloud Skipper, enables developers to design, deploy, and manage event‑stream pipelines on Apache Kafka, covering ecosystem overview, pipeline components, Docker‑based local setup, stream creation, debugging, monitoring, and integration of Kafka Streams applications.

Apache KafkaEvent StreamingKubernetes

0 likes · 15 min read

Spring Cloud Data Flow: Building and Deploying Event Stream Pipelines with Apache Kafka (Part 3)