6 Best Kafka Alternatives: 2022’s Must-know List

on Data Integration, Data Streaming, Kafka • January 11th, 2022 • Write for Hevo

Kafka Alternatives FI

It’s no secret that Kafka was the first event-streaming platform that helped organizations effectively harness the power of real-time data. Over the years, it has become the go-to solution for handling and processing streaming data for quick decision-making. Despite its widespread adoption, Kafka may not always be the best choice for message queuing. Kafka requires a lot of Memory and Storage, so setting up a multi-node cluster for testing purposes on a standalone workstation can be tricky. Organizations and users are thus shifting to Kafka Alternatives that are more user-friendly.

Table of Contents 

Prerequisites

  • A basic understanding of data streaming infrastructure 

Understanding Kafka 

Kafka Alternatives: Kafka logo
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Kafka is an Open-Source software program that lets you store, read, and analyze streaming data. It is free for everyone to use and is supported by a large community of users and developers who consistently contribute to new features, updates, and support. As a “Distributed” system, Kafka can run on several servers to leverage different servers’ processing power and storage capacity.

As a part of its original design, Kafka was intended to monitor the behavior of users on websites. A complete picture of user behavior can be obtained by analyzing clickstream data after every session (where do users navigate on the website and what functions they use). Using this information, you can predict which articles or products a visitor would be interested in.

To further extend its capabilities, Apache Kafka supports integrations with Apache Flume, Apache Spark Streaming, Apache Storm, and HBase for real-time research, analysis, and streaming data processing to extend its capabilities further.

Key Features of Kafka 

1) Scalability

With Apache Kafka, users can scale in all four dimensions: Event Producer, Event Processor, Event Consumer, and Event Connector. You can scale effectively with Kafka without experiencing downtime.

2) Persistent for short-run

The retention policy for Kafka is configured by default to be seven days and can be changed as per user. Using Kafka, you can store your data for Short Periods before erasing the oldest values.

3) Replication

Kafka MirrorMaker supports cluster replication. Multiple Data Centers or Cloud Regions can receive messages via replication features. The system can be used in active/passive scenarios to back up and recover data or inactive/passive scenarios to place data closer to your users or support local data requirements.

4) Reliability and Durability

Kafka maintains a replica of its messages on disk, allowing intra-cluster replication. This makes Kafka a highly durable messaging system. Kafka is also highly reliable due to its distributed, partitioned, replicated, and fault-tolerant nature.

5) Extensibility 

Kafka has gained popularity among other applications in recent years, prompting many applications to design their systems for easy integration. Since Kafka can be plugged into several applications, you can seamlessly add new functionality and execute your initiatives.

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Top 6 Kafka Alternatives

Kafka is a widely used publish-subscribe-messaging service known for managing large volumes of information, handling both online and offline messages. However, Kafka has some shortcomings such as slow speeds, message tweaking, lesser message paradigms, and more, thereby increasing the usage of Kafka Alternatives.

Below is a comprehensive list of top Kafka Alternatives that can be used to manage real-time data feeds while maintaining low latency and high throughput:

1) Amazon Kinesis 

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Amazon Kinesis streams, collects, processes, and analyzes video and data streams in real-time. It provides timely information and allows for complete flexibility and scalability. With Kinesis, you can ingest various data types, including audio, video, and app logs.

Kinesis enables streaming applications to be managed without additional infrastructure management. This highly scalable platform can process data from various sources with low latency. Known for its speed, ease of use, reliability, and capability of cross-platform replication, Amazon Kinesis is one of the most popular Kafka Alternatives. It is used for many purposes, including geospatial data connected to users, social networking data, and IoT sensors.

Amazon Kinesis has different pricing editions based on Shard Hours and PUT Payload Units. When using Kinesis, you pay for the number of hours or Payload units you use and the time you use them. One shard costs $0.015 per hour or $0.36 per day, and 1 million PUT Payload Units cost $0.014. However, the pricing may vary from region to region.

2) RabbitMQ

Kafka Alternatives: Rabbit MQ
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RabbitMQ is an open-source message broker that can be easily deployed on the cloud. Besides supporting asynchronous messaging services, it offers a great developer experience with Java, Go, Python, Ruby, etc. Since developers widely use Kafka with multiple languages, it runs on different operating systems and cloud infrastructure. RabbitMQ can also be deployed in a distributed environment for high availability.

Due to RabbitMQ’s lightweight design, it can be easily deployed on public and private clouds. RabbitMQ is backed not only by a robust support system but also offers a great developer community. Since it is open-source software it is one of the best Kafka Alternatives and RabbitMQ is free of cost.

3) ActiveMQ

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ActiveMQ is a flexible, open-source, multi-protocol messaging broker that supports many protocols. This makes it easy for developers to use a variety of languages and platforms. The AMQP protocol facilitates integration with many applications based on different platforms. However, ActiveMQ’s high-end data accessibility capabilities are complemented by its load balancing, resource allocation, and management capabilities. ActiveMQ can be seamlessly incorporated into nearly any application with its simple but powerful message semantics. ActiveMQ is known for integrating services across multiple apps and efficiently allocating resources.

Apache ActiveMQ software is one the best free and open-source software Kafka Alternatives under the Apache 2.0 ASF license.

4) Red Hat AMQ

Kafka Alternatives: Red Hat AMQ logo
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With a robust suite of components based on communities like Apache Kafka and ActiveMQ, Red Hat AMQ offers a secure and lightweight solution message delivery and one of the best Kafka Alternatives. Compared to most streaming tools, Red Hat AMQ has faster execution and offers a flexible messaging tool that allows instant communication. Consequently, Red Hat AMQ effectively meets organizational needs and integrates business apps across organizations.

Providing real-time insight and seamless connectivity with IoT devices, Red Hat AMQ offers instant information from data sources. With Kafka and ActiveMQ combined, Red Hat AMQ deals with long-running queries effectively. Due to its two-pronged benefits, Red Hat AMQ is an ideal alternative to Apache Kafka.

Red Hat AMQ has two subscription plans: 16-Core-Standard and 16-Core-Premium, both valid for one year. The Standard subscription costs $28,800, and the Premium subscription costs $43,200. 

5) IBM MQ

Kafka Alternatives: IBM MQ
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IBM MQ provides enterprise-level messaging capabilities, allowing secure and efficient communication between applications. The system provides seamless communication across projects, efficiently handling multiple transactions. It retains the one-and-only-once delivery pattern, thereby ensuring Security.

IBM MQ is one of the best Kafka Alternatives which has an easy-to-use Interface and High Reliability and Data Security. It also facilitates the interoperability between various applications, either within or outside the organization. IBM MQ allows developers to focus on critical issues and manage any changes to transaction volumes asynchronously due to its simple structure.

IBM MQ offers four plans with different virtual processor cores allocation, each core costing $0.92 per hour. The four plans are named: Extra Small, Small, Medium, and Large.

6) Amazon SQS

Kafka Alternatives: SQS logo
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Amazon SQS (Simple Queue Service) is a messaging queueing service that is fully managed for Distributed Systems, Serverless Applications, and Microservices. It is known for the separation of components and the development of asynchronous processes. With its excellent SDK and functional console, it is favored by developers.

Amazon SQS offers standard features such as dead-letter queues and costs allocation tags. With Amazon SQS, you can access the web services API in any programming language that supports the AWS SDK.

Amazon SQS has two queue plans based on monthly requests. The first one million requests per month are free of cost for Standard and FIFO queues. The price may vary depending on the region and the number of requests per month. Over 200 Billion Requests/Month can cost $0.32 and $0.42 for Standard and FIFO queues, respectively.

Conclusion

In this article, you learned about Kafka, its features, and some top Kafka Alternatives. Even though Kafka is widely used, the technology segment has advanced to the point where other options can overshadow Kafka’s cons. There are various options available for choosing a stream processing solution. Organizations are increasingly embracing event-driven architectures powered by event streaming and stream processing technologies as the demand for real-time data grows. If you want to transfer data from Kafka or any of the Kafka Alternatives to your desired destination, the Hevo is the best choice for you.

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Hevo Data provides its users with a simpler platform for integrating data from 100+ sources such as Kafka for Analysis. It is a No-code Data Pipeline that can help you combine data from multiple sources including most of the Kafka Alternatives. You can use it to transfer data from multiple data sources into your Data Warehouses, Database, or a destination of your choice. It provides you with a consistent and reliable solution to managing data in real-time, ensuring that you always have Analysis-ready data in your desired destination.

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