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- Kafka is more than a simple message broker. It offers additional capabilities like stream processing, durability, flexible messaging semantics and better scalability and performance than traditional brokers. While its superior characteristics increase complexity, the trade-off seems justified.
thenewstack.io/decoding-kafka-why-its-worth-the-complexity/Decoding Kafka: Why It’s Worth the Complexity - The New Stack
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What is Kafka and how does it work?
What is Apache Kafka & why should you use it?
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Is Kafka worth it?
Why Kafka? From data pipelines and microservices to data streaming and analytics, learn the advantages Kafka brings for different use cases in all industries.
Nov 3, 2023 · Since its inception over a decade ago, Kafka has matured into the de facto standard for data streaming, because it has the following advantages: Scalability — up to trillions of messages per day, thousands of topics split into tens of thousands of partitions and hundreds (or even thousands) of brokers.
Apr 15, 2024 · Today, we'll uncover what Kafka is and why it's becoming a cornerstone in modern data processing. Imagine a bustling city where information is constantly flowing. Apache Kafka is like the central nervous system of this city, designed to handle this massive flow of data with ease and efficiency.
Oct 1, 2024 · Kafka is optimized for both write and read operations, contributing to its exceptional speed in handling data. When it comes to writing, Kafka benefits from its append-only storage mechanism. Messages are appended to the end of a partition, and this sequential write operation is highly efficient.
- What, Why, When to Use Apache Kafka, with An Example
- What Is Apache Kafka
- Why Use Apache Kafka
- Common Use Cases
- Recap
- Conclusion
I have seen, heard and been asked questions and comments like The objective of this post is to get you up to speed with what Apache Kafka is, when to use them and the foundational concepts of Apache Kafka with a simple example.
First let’s understand what Apache Kafka is. According to the official definition, it is a distributed streaming platform. This means that you have a cluster of connected machines (Kafka Cluster) which can 1. Receive data from multiple applications, the applications producing data(aka messages) are called producers. 2. Reliably store the received d...
In order to understand why Apache Kafka is popular with streaming apps, lets understand what is generally used, and why Apache Kafka is a better choice for certain use cases.
The RESTfulservices model works fine for most cases. Let’s go over the use cases below and try to think of efficient ways to solve them 1. Let’s assume our application has 10Million users and we want to record user actions(hover, move, idle, etc) every 5 seconds. This will create 120Million user action events per minute. In this case we don’t have ...
In this post we saw 1. What Apache Kafka is 2. When to use Apache Kafka with a few common use cases 3. Apache Kafka concepts - Producer, Topic, Broker, Consumer, Offset and auto commit There are more advanced concepts like partition size, partition function, Apache Kafka Connectors, Streams API, etc which we will cover in future posts.
Hope this article gives you a good introduction of Apache Kafka and insights into when to use and not use it. Let me know if you have any comments or question in the comments section below.
Jan 17, 2024 · Apache Kafka is a distributed streaming platform designed to handle large volumes of real-time data. It’s an open-source system used for stream processing, real-time data pipelines and data integration. LinkedIn originally developed Kafka in 2011 to handle real-time data feeds.
Dec 15, 2017 · Summary. Apache Kafka is a distributed streaming platform capable of handling trillions of events a day. Kafka provides low-latency, high-throughput, fault-tolerant publish and subscribe pipelines and is able to process streams of events.
