In modern large data environments, the sending and processing of messages becomes very important.

The elephant in the message-sending world is Kafka.

Kafka is directly related to Kinesis

Before comparing Kafka with Kinesis, we need to know something about Kinesis.

What is a Kafka

Apache Kafka is an open source, distributed, and scalable publish-subscribe messaging system. The organization responsible for the Software is the Apache Software Foundation. The code, written in Scala, was originally developed by the LinkedIn Company. It opened source in 2011 and became Apache’s top project.

The project aims to provide a unified low-latency platform that can process data feeds in real time. It becomes increasingly valuable for different enterprise infrastructures that require integration between systems. Systems that want to integrate can publish or subscribe to specific Kafka topics according to their needs.

Kafka is influenced by transaction logging. The idea behind Apache Kafka is to be a scalable message queue with a structure similar to transaction logging.

The platform is designated for real-time data streaming.

Kafka allows you to organize data under specific topics.

In short, Kafka’s message processing capability is fast, very fast.

What is a Kinesis

Simply put, Kinesis is an implementation of THE AWS cloud platform.

With self-deployed Kafka, you don’t have to maintain the hardware platform, you don’t have to pay for the hardware and you can deploy very quickly.

Amazon Kinesis enables you to easily collect, process, and analyze real-time streaming data so that you can gain timely insights and respond quickly to new information. Amazon Kinesis provides a variety of core features that allow you to process streaming data of any size economically and efficiently, while providing flexibility that allows you to select the tool that best meets your application’s needs.

With Amazon Kinesis, you can access real-time data such as video, audio, application logs, and website clickstreams, as well as IoT telemetry data for machine learning, analytics, and other applications.

How to choose

Perhaps the following comparison will help you make some decisions for children and companies with choice problems.

The main difference

Kafka is an open source distributed messaging solution, while Kinesis is a hosted platform provided by Mazon.

In Kafka, you are responsible for installing and managing the cluster, as well as ensuring high availability, persistence, and failure recovery. If you’re using Kinesis, you don’t have to worry about managed software and resources.

While you can easily learn Kafka by installing it on your local system, Kinesis is not.

Pricing in Kinesis depends on the number of shardings you use. If you plan to keep messages for a long time, you must also pay an additional fee.

For Kafka, the cost depends largely on the number of brokers you use. Kafka also requires a DevOps team to maintain, which can be costly.

However, with Kafka, as long as you don’t run out of storage space, you can keep messages for longer without paying extra.

Although Both Kafka and Kinesis consist of producers, the Kafka producer writes messages to the topic, while the Kinesis producer writes data to the KDS.

Kinesis also imposes certain limits on message size and message consumption rate.

The maximum message size in Kinesis is 1 MB, while Kafka can be much larger.

In Kinesis, you can consume up to five times per second, and up to 2 MB per fragment, resulting in only 1000 records written per second.

Kafka imposes no implicit restrictions, so rates are determined by the underlying hardware, and you can even do unlimited fast data writes.

In terms of security, Kafka provides a number of client-side security features such as data encryption, client authentication, and client authorization, while Kinesis provides server-side encryption through AWS KMS master keys to encrypt data stored in the data stream.

With server-side encryption, it is difficult to perform client-side encryption.

Server-side encryption provides a second layer of security on top of client-side encryption.

consideration

Are you still a little confused after seeing so much above?

In fact, leaving the data volume to talk about the plan is playing rogue.

The simple point is that the Kinesis is quick to pick up, and if you don’t have the technical muscle, you can use it with a single click from the AWS console.

There are costs and curves to deploying Kafka. First, Kafka relies on ZooKeeper to run, and ZooKeeper’s minimum operating environment requires three servers. If ZooKeeper needs to scale, it needs five servers, because ZooKeeper needs to maintain high availability. You need an odd number of servers.

If you deploy 4 servers to ZooKeeper, ZooKeeper will work just as well as 3.

This leads to use and learning costs.

If you have tens of thousands of messages a day in a given cycle and few technicians at hand, you can use either one, and the Kinesis is probably a little easier and faster to get started.

If you’re using 10,000 messages per minute, you might want to consider Kafka, because Kinesis isn’t cheap with the number of messages, and there’s a limit to how long messages can be kept.

Kafka’s extensibility is entirely possible by extending the underlying hardware, and there are maintenance costs involved.

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