Kafka vs Kinesis: Select

Streams for Everybody

You probably have come this far it means you’ve gotten already thought of or are contemplating utilizing occasion streaming in your knowledge structure for the big variety of advantages it may well provide. Or maybe you’re searching for one thing to assist a Information Mesh initiative as a result of that’s all the trend proper now. In both case, each Amazon Kinesis and Apache Kafka will help however which one is the appropriate match for you and your objectives. Let’s discover out!

Actual fast disclaimer, I presently work at Rockset however beforehand labored at Confluent, an organization recognized for constructing Kafka based mostly platforms and cloud companies. My expertise and understanding of Kafka is way deeper than Kinesis however I’ve made each try to offer a principally unbiased comparability between the 2 for the needs of this text.

Software program or Service

Apache Kafka is Open Supply Software program, ruled by the Apache Software program Basis and licensed beneath Apache License Model 2.0. You’ll be able to have a look at the supply code, deploy it wherever you need and even fork the supply code, create a brand new product and promote it! Amazon Kinesis is a totally managed service out there on AWS. The supply code is just not out there and that’s okay, nobody’s judging KFC for holding their recipe secret. When it comes to software program deployment and administration methods, Kafka and Kinesis couldn’t be extra totally different. This elementary distinction between software program and repair makes them attention-grabbing to match since Kinesis has no true Open Supply various and Kafka has a number of non-AWS managed service choices together with Aiven, Instaclustr and Confluent Cloud. This inevitably makes Kafka the extra versatile possibility between the 2 if hedging in opposition to an AWS-only structure.

Accessible or Handy

As with many Open Supply tasks, Kafka gained reputation by being simply accessible to an viewers of engineers and builders who had sufficient {hardware} to unravel their drawback however couldn’t discover the appropriate software program. Alternatively, Kinesis has turn out to be one of many prime cloud-native streaming companies largely based mostly on its comfort and low barrier to entry, particularly for current AWS clients. For probably the most half these facets have continued for each events and you could find numerous totally different variations of Kafka with an unlimited and diverse ecosystem. Whereas Kinesis stays land locked within the AWS ecosystem, it’s nonetheless extraordinarily straightforward to get began with and has tight coupling with a number of key AWS companies like S3 and Lambda. Providers like Confluent Cloud and AWS Managed Streaming for Kafka (MSK) are makes an attempt at growing the comfort of Kafka within the cloud (Confluent Cloud being probably the most mature possibility) however in comparison with Kinesis, they’re nonetheless works in progress.

Architect or Developer

As with all analysis we also needs to take into account our viewers. For an architect trying on the huge image, Kafka typically appears engaging for each its flexibility and trade adoption. The Kafka API is so pervasive even different cloud-native messaging companies have adopted it (see Azure Occasion Hubs). Though as a developer one could also be pressured right into a extra tactical resolution in want of a well-known end result that makes Kinesis an apparent selection. Kinesis additionally has a developer-friendly REST-based API and a number of other language particular shopper libraries. Kafka additionally has many language particular libraries in the neighborhood however formally solely helps Java. In different phrases, in case you are studying this text and you’ll want to decide tomorrow, that is likely to be too quickly to think about a strategic platform like Kafka. If you have already got an AWS account, you may have a extremely scalable occasion streaming service at the moment with Kinesis.

Huge or Quick

Efficiency in a streaming context is commonly about two issues: latency and throughput. Latency being how rapidly knowledge will get from one finish of the pipe to the opposite and throughput being how huge (assume circumference) the pipe is. Generally, each Kafka and Kinesis are designed for low-latency and high-throughput workloads and there are many sensible examples on the market in case you care to seek for them. So they’re each quick however the actual distinction in efficiency between the 2 comes from an idea known as fanout. Since its inception Kafka was designed for very excessive fanout, write an occasion as soon as and browse it many, many occasions. Kinesis has the flexibility to fanout messages however it makes very particular and well-known limits about fanout and consumption charges. A fanout ratio of 5x or much less is often acceptable for Kinesis however I might look to Kafka for something larger.

Partitions or Shards

So as to obtain scalability each Kafka and Kinesis break up knowledge up into remoted models of parallelism. Kafka calls these partitions and Kinesis calls them shards however conceptually they’re equal of their nature to permit for larger ranges of throughput efficiency. Each have documented limits across the most variety of partitions and shards however these are altering typically sufficient that it’s extra related to consider per unit numbers. For details about per partition throughput we’ve to take a look at Confluent Cloud documentation as there isn’t a commonplace for Kafka. On this case Confluent Cloud supplies a max 10MB/s write and max 30MB/s learn per partition. Kinesis documentation has a clearer however decrease quantity per shard at 1MB/s write and 2MB/s learn. This doesn’t inherently imply that partitions are higher than shards however when interested by your capability wants and prices, it’s essential to start out with what number of of those models of parallelism you’re going to want as a way to meet your necessities.

Secured or Secure

Kafka and Kinesis each have comparable security measures like TLS encryption, disk encryption, ACLs and shopper permit lists. Sadly for Kafka it’s the lack of enforcement of those options that comes as a detriment. Until you’re utilizing Confluent Cloud, Kafka has these options as choices whereas Kinesis for probably the most half mandates them. That provides Kinesis an enormous safety benefit and like many different AWS companies, it integrates very nicely with current AWS IAM roles, making safety fast and painless. And in case you are pondering, nicely I don’t want all of these issues as a result of I’m self managing Kafka in my non-public community then you’ll want to cease studying this and go examine Zero Belief. For these coming back from their Zero Belief replace and the remainder of us, the underside line is that each Kafka and Kinesis will be secured however it’s Kinesis and different managed cloud companies which are inherently safer as it’s a part of their cloud rigor.


Right here’s a fast desk that summarizes among the dialogue from above.


In case you pressured me to decide on between Kafka or Kinesis, I might select Kafka each day and twice on Sunday. The reason is that as somebody who’s extra of an architect, I’m trying on the huge image. I is likely to be selecting an enterprise commonplace occasion retailer the place I must separate the selection of Cloud supplier from my selection for a standard knowledge trade API. After all, within the absence of competing managed companies for Kafka and an current AWS account I might in all probability lean in the direction of Kinesis to enhance my time to market and decrease operational burden. The context of the scenario issues greater than the characteristic set of every expertise. Everybody has a novel and attention-grabbing scenario and I hope with some insights from this text, some second opinions and hands-on expertise, you can also make a choice that’s greatest for you. I don’t assume you’ll be dissatisfied in both case as each applied sciences have stood the check of time, doubtless solely to be supplanted by one thing completely new that none of us have heard of but (simply ask JMS).

Rockset is the main real-time analytics platform constructed for the cloud, delivering quick analytics on real-time knowledge with stunning effectivity. Rockset supplies built-in connectors to each Kafka and Kinesis, so customers can construct user-facing analytics on streaming knowledge rapidly and affordably. Study extra at rockset.com.

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