AWS Kinesis vs Kafka Apache

Both Apache Kafka and AWS Kinesis are data streaming services that are highly commendable in their respective fields. Your experience will depend on your specific needs and the use cases that you plan to implement.
AWS Kinesis is sometimes referred to as Apache Kafka’s rebranding service. This is not true as both services have different features to meet the needs of clients. This article will briefly explain the core concepts of Kinesis and Kafka to help you see how they differ.
Although AWS Kinesis is offering similar data streaming services to Apache Kafka, their internal functions differ from each other. This Kinesis vs Kafka article will explain the differences and provide a detailed explanation of the fundamental knowledge and definitions.
Definition of AWS Kinesis
AWS Kinesis is well-known for its key capabilities, which include video streams, data firehoses, data analytics, and stream data. Kinesis is compared to Kafka because of its data streaming capability. Let’s put it in the spotlight. AWS Kinesis’ data streaming capability is designed to collect and process large amounts of data in real time. This functionality is identical to Apache Kafka.
AWS Kinesis will also help you to use its key potential to stream data at any scale, and in a cost-effective way. You can also choose the tools that best suit your application needs.
Learn more about AWS Kinesis. From the basics to the advanced!
AWS Kinesis doesn’t require you to wait for data to be collected before you can begin processing. Instead, it analyzes and processes the data right away, so you can respond to it immediately.
The architecture of Kinesis Data Streams has high-level features. It is as follows:
Producer begins with data ingestion onto Kinesis Data Stream. Kinesis then offers a producer library to simplify the application development. AWS Kinesis can help you achieve high throughput for KDS.
KDS usually consists of several shards. Each shard consists of a particular sequence of data records. Each piece of data in the stream is composed of a data blob and a partition key.
Kinesis lets users build applications using its APIs, Client Library(KCL), and data analytics. The KDS records are available to the consumers who then begin further processing.
Definition of Apache Kafka
Apache Kafka is an open-source data streaming platform that was originally developed by LinkedIn. It has been donated to the Apache Software Foundation. The platform is written in Scala and Java. Apache Kafka’s APIs allow producers to integrate data streams into record logs.
These logs of records are also called topics! Each topic is a partition of these logs that is immutable, and is ordered. These topics are intended for consumers to subscribe to. These are the core APIs of Kafka:
The producer API allows apps to send data streams across the Kafka Cluster to various topics.
The Kafka Cluster’s consumer API allows apps to access data streams from different topics.
The Streams API allows data streams to be transformed from input to output topics.
Connect API allows you to implement several connectors that pull data from any application to Kafka, or vice versa.
AdminClient API allows inspection and management of topics, brokers, and other Kafka objects.
Apache Kafka is a data streaming platform that deals with large amounts of data in real time. It provides high throughput for publishing and subscribing. The distributed systems can scale up without any downtime in any of four dimensions.
Apache Kafka will not allow data loss or downtime, even if the system is in trouble. However, Kafka needs some human support to install and manage the clusters. Users might need to put in additional effort to configure and scale the functionality to meet their availability, recovery, durability, and other requirements.
AWS Kinesis vs Apache Kafka
Now that you have a basic understanding of Kafka and Kinesis, it is time to watch the Kinesis vs Kafka fight on the aspects of their differentiating factors. These two data streaming platforms have different criteria that highlight the differences. The battle between Kafka and Kinesis begins!
1. Data Retention
AWS Kinesis can store data for up to 7 days. Apache Kafka can have a longer retention period, as users can configure these retention periods.
2. Time to set-up and operations
Apache Kafka takes comparatively a little while