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Pulsar vs Kinesis

The data-driven business decision culture extended beyond Fortune 500 companies. With so many assets generating data in real-time, companies of all sizes started collecting, analyzing, and storing it to improve their processes. To excel at it, companies need to use sophisticated software solutions called distributed messaging systems. Today, we are going to compare two messaging queue systems – Pulsar vs Kinesis. We will try to provide you with all the information you need to decide which solution has more to offer in terms of processing more data and through various data pipelines.

What is Pulsar

Pulsar is developed on Kafka, and many consider it an updated and far more superior version of Kafka. Initially, Kafka was created by LinkedIn as a messaging queue system. LinkedIn opened sourced it in 2011, and the system evolved into a full-fledged event streaming platform. 

Yahoo’s team took Kafka and used it to develop Pulsar. At Yahoo, Pulsar was used as a messaging platform connecting all critical Yahoo apps. Yahoo open-sourced it in 2016. In 2018, Pulsar became a top-level project at Apache Software Foundation.

Today, Apache Pulsar is a high-performance and multi-tenant solution for server-to-server messaging. You can use it to build real-time streaming apps and data pipelines. Big companies such as Verizon Media, Nutanix, Splunk, and Tencent quickly picked it up and started using it. Why? Because Apache Pulsar offers a variety of top-notch functions and features:

  • Easy deployment without a need to set up a stream processing engine on your own;
  • Horizontal scalability enables users to expand the system’s capacity to hundreds of nodes;
  • Extremely low latency of < 5ms even at scale;
  • Easily configurable geo-replication across multiple regions;
  • A multi-tenant system with support for quotas, authorization, authentication, and isolation;
  • Apache BookKeeper enabled persistent message storage;
  • APIs for Python, Node.js, Java, Go, C#, C++, and WebSocket;
  • Enables deployment on Kubernetes;

What is Kinesis

Kinesis is a service for processing big data in real-time offered through Amazon Web Service (AWS). You can use Kinesis to process petabytes of data efficiently. With Kinesis, you can capture data from various sources ranging from social media feeds to financial transactions. It features real-time operational decision making which significantly simplifies the development of apps. 

A good thing about Kinesis is that it supports various types of data such as video, audio, textual, IoT telemetry, and website clickstream data. It enables you to analyze and process the data as it comes, thus significantly speeding up your processes. 

Kinesis Data Streams is a durable and scalable real-time data streaming service. It ingests and stores data streams for further processing. KDS supports connection to several real-time analytics applications. One of the better perks KDS has to offer is security, as it enables you to secure data at rest with AWS KMS master keys and server-side encryption. 

Key Considerations: Pulsar vs Kinesis

When choosing a distributed messaging solution for a business use case, you need to consider several things – price, scalability, and versatility of a solution in terms of future workloads. With this in mind, let’s see the outcome of the Pulsar vs. Kinesis comparison.

Price

When it comes to the price of Pulsar vs Kinesis, there are a few things you should keep in mind. Let’s address Pulsar first. Pulsar is open source, meaning that you can use it for free. However, it is not one of those out-of-the-box solutions. It means that it will cost you to implement Pulsar because you need to have a proper in-house infrastructure and proficient human resources to configure it. Down the line, you will need to pay for maintenance as well.

Once set up, you will be able to start using Pulsar, and there will be no hidden costs except the before-mentioned maintenance and requested customizations. 

On the other hand, Amazon Kinesis is a hosted system meaning that you won’t need to handle the installation personally. The system runs on Amazon servers. You will need to set it up, though, which requires substantial knowledge. If you don’t have someone with the skillset on your payroll, you will have to outsource it, which can be expensive and time-consuming. You will also have to do it again if you need to customize the configuration.

Lastly, Amazon offers a “pay-as-you-go” plan with Kinesis. It comes with provision-based pricing. While it enables you to customize your service package completely, you will have to pay for the provisioned clusters even if you don’t use them at all. 

Scalability

Both Pulsar and Kinesis are scalable. Pulsar is made to be scalable from the ground up. It uses AI to go through massive amounts of data in no time and with no downtime. It delivers unparalleled scalability across all four dimensions, including connectors, consumers, processors, and producers. Thanks to unique architecture, scaling is stable, and the system is durable and fault-tolerant. 

Kinesis is also scalable and able to handle any amount of data you throw at it. It can collect and process data from countless resources and still do it with consistently low latencies. The only trick is to know how many resources you will need. Kinesis Data Streams costs pile up with more resources you use, and you will be charged per Shard Hour even if you don’t end up using it. 

Pulsar and Kinesis for Future Workloads

In terms of scalability, both Kinesis and Pulsar look promising when it comes to getting ready for future workloads. However, few things make Pulsar a better solution for real-time data streaming

First, you need to take pricing under consideration. Being able to custom-tailor the service package according to your own needs is neat, but you can never be 100% sure how many clusters you need. Paying for those extra shards per hour can be expensive and not sustainable in the long run. With Pulsar, you can scale up and down seamlessly.

Also, Kinesis comes with a 7-days limitation on the maximum retention period per shard. Pulsar does not. If you need to keep messages for more than seven days, Pulsar is your go-to option. 

With more enterprises building architectures which include processing data pipelines in real-time, you should consider getting a more versatile and scalable solution. At the moment, Pulsar is ahead of Kinesis in these departments. The only downside is having to install, configure, and maintain it manually. This is where the Pandio managed Pulsar service comes in to help you get the best of both worlds.

With Pandio, you will be able to rip all the benefits Pulsar has to offer without writing a single line of code or having to worry about updates and maintenance. You will also be able to control your expenses as you will be paying only for what you use. If this sounds interesting, you should check out how Pandio can help you get your organization ready for future workloads.

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