Understanding Kafka Architecture: Topics, Partitions, Producers, Consumers, Offsets, and Transactions

Kafka is a high‑performance distributed message queue that uses topics, partitions, and replicas for scalability, with producers writing messages, consumers reading them via consumer groups, and advanced features such as offset management, delivery semantics, rebalancing, and exactly‑once transactional processing, all coordinated by Zookeeper.

ConsumersDistributed MessagingExactly-Once

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Understanding Kafka Architecture: Topics, Partitions, Producers, Consumers, Offsets, and Transactions

Big Data Technology & Architecture

Mar 1, 2022 · Big Data

Apache Pulsar Overview: Architecture, Components, and Usage

This article provides a comprehensive overview of Apache Pulsar, detailing its multi‑tenant architecture, core components such as brokers and BookKeeper, message handling features, producer and consumer configurations, comparison with Kafka, and operational considerations for deployment.

Apache PulsarBookKeeperConsumers

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Apache Pulsar Overview: Architecture, Components, and Usage

Open Source Linux

Jul 17, 2021 · Big Data

Master Kafka Basics: Topics, Partitions, Producers & Consumers Explained

This article provides a clear, visual guide to Kafka’s core concepts—including producers, consumers, topics, partitions, consumer groups, message ordering, and the underlying ZooKeeper‑managed cluster architecture—helping readers grasp how Kafka enables reliable, scalable stream processing.

Big DataConsumersPartitions

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Master Kafka Basics: Topics, Partitions, Producers & Consumers Explained

Big Data Technology Architecture

Jul 9, 2019 · Big Data

Kafka Best Practices for High Throughput: 20 Recommendations

This article presents New Relic's 20 best‑practice recommendations for operating Apache Kafka at high throughput, covering partitions, consumers, producers, and brokers, and explains key concepts, configuration tuning, monitoring, and architectural considerations to ensure reliable, scalable streaming pipelines.

BrokersConsumersHigh Throughput

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Kafka Best Practices for High Throughput: 20 Recommendations

Java Backend Technology

Nov 23, 2018 · Big Data

20 Proven Kafka Best Practices for High‑Throughput Enterprise Deployments

This article presents 20 practical best‑practice recommendations—from partition sizing and consumer tuning to producer configuration and broker optimization—to help engineers build scalable, reliable, and high‑throughput Apache Kafka clusters for large‑scale applications.

Apache KafkaBrokersConsumers

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20 Proven Kafka Best Practices for High‑Throughput Enterprise Deployments

dbaplus Community

Nov 20, 2018 · Backend Development

20 Proven Kafka Best Practices for High‑Throughput Clusters

This guide presents New Relic’s 20 practical best‑practice recommendations—covering partitions, consumers, producers, and brokers—to help engineers design, tune, and monitor Apache Kafka deployments for reliable, high‑throughput performance.

BrokersConsumersHigh Throughput

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20 Proven Kafka Best Practices for High‑Throughput Clusters