Apache Kafka vs. Mirantis Kubernetes Engine

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Kafka
Score 8.4 out of 10
N/A
Apache Kafka is an open-source stream processing platform developed by the Apache Software Foundation written in Scala and Java. The Kafka event streaming platform is used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.N/A
Mirantis Kubernetes Engine
Score 9.3 out of 10
N/A
The Mirantis Kubernetes Engine (formerly Docker Enterprise, acquired by Mirantis in November 2019)aims to let users ship code faster. Mirantis Kubernetes Engine gives users one set of APIs and tools to deploy, manage, and observe secure-by-default, certified, batteries-included Kubernetes clusters on any infrastructure: public cloud, private cloud, or bare metal.
$500
per year per node
Pricing
Apache KafkaMirantis Kubernetes Engine
Editions & Modules
No answers on this topic
Free
$0.00
per year
Basic
$500.00
per year
Offerings
Pricing Offerings
Apache KafkaMirantis Kubernetes Engine
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details—These pricing options are compatible with Linux or Windows Server and are per year, per node. The basic version requires maximum online purchase not to exceed 50 nodes. Support/professional services are not included.
More Pricing Information
Community Pulse
Apache KafkaMirantis Kubernetes Engine
Considered Both Products
Apache Kafka
Chose Apache Kafka
Kafka is not a real messaging broker implementation as RabbitMQ or TIBCO EMS/JMS are. Although it can be used as messaging, we like the idea behind the Kafka (data isn't "passing by," instead it remains centra, so the client can revisit the data if necessary). This also …
Mirantis Kubernetes Engine

No answer on this topic

Top Pros
Top Cons
Best Alternatives
Apache KafkaMirantis Kubernetes Engine
Small Businesses

No answers on this topic

Portainer
Portainer
Score 9.3 out of 10
Medium-sized Companies
IBM MQ
IBM MQ
Score 9.0 out of 10
IBM Cloud Kubernetes Service
IBM Cloud Kubernetes Service
Score 9.2 out of 10
Enterprises
IBM MQ
IBM MQ
Score 9.0 out of 10
IBM Cloud Kubernetes Service
IBM Cloud Kubernetes Service
Score 9.2 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache KafkaMirantis Kubernetes Engine
Likelihood to Recommend
8.3
(18 ratings)
8.3
(37 ratings)
Likelihood to Renew
9.0
(2 ratings)
9.1
(1 ratings)
Usability
10.0
(1 ratings)
8.0
(2 ratings)
Support Rating
8.4
(4 ratings)
7.8
(3 ratings)
User Testimonials
Apache KafkaMirantis Kubernetes Engine
Likelihood to Recommend
Apache
Apache Kafka is well-suited for most data-streaming use cases. Amazon Kinesis and Azure EventHubs, unless you have a specific use case where using those cloud PaAS for your data lakes, once set up well, Apache Kafka will take care of everything else in the background. Azure EventHubs, is good for cross-cloud use cases, and Amazon Kinesis - I have no real-world experience. But I believe it is the same.
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Mirantis
[Mirantis Cloud Native Suite (Docker Enterprise)] is the most advanced tool till now, which works as a VMs
and separates any single application from the dependencies. Also, this tool is
helping me in the agile development of the processes. It is strongly recommended to
almost all major organizations.
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Pros
Apache
  • Really easy to configure. I've used other message brokers such as RabbitMQ and compared to them, Kafka's configurations are very easy to understand and tweak.
  • Very scalable: easily configured to run on multiple nodes allowing for ease of parallelism (assuming your queues/topics don't have to be consumed in the exact same order the messages were delivered)
  • Not exactly a feature, but I trust Kafka will be around for at least another decade because active development has continued to be strong and there's a lot of financial backing from Confluent and LinkedIn, and probably many other companies who are using it (which, anecdotally, is many).
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Mirantis
  • Containers - Docker is the go-to when using Containers, which are super useful if you need an environment that works both for Windows and Linux
  • Efficiency - Docker is very lightweight and doesn't demand too much from your CPU or server
  • CI/CD - Docker is excellent for plumbing into your build pipeline. It integrates nicely, is reliable, and has an easy set up.
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Cons
Apache
  • Sometimes it becomes difficult to monitor our Kafka deployments. We've been able to overcome it largely using AWS MSK, a managed service for Apache Kafka, but a separate monitoring dashboard would have been great.
  • Simplify the process for local deployment of Kafka and provide a user interface to get visibility into the different topics and the messages being processed.
  • Learning curve around creation of broker and topics could be simplified
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Mirantis
  • Containers are often opaque - if a container doesn't work out of the box, it's messy to fix.
  • Logging is complexified by the multiple containers and logs are often not piped to places you expect them to be.
  • Networking is complexified due to internal port mapping between containers, etc.
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Likelihood to Renew
Apache
Kafka is quickly becoming core product of the organization, indeed it is replacing older messaging systems. No better alternatives found yet
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Mirantis
No answers on this topic
Usability
Apache
Apache Kafka is highly recommended to develop loosely coupled, real-time processing applications. Also, Apache Kafka provides property based configuration. Producer, Consumer and broker contain their own separate property file
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Mirantis
Docker's CLI has a lot of options, and they aren't all intuitive. And there are so many tools in the space (Docker Compose, Docker Swarm, etc) that have their own configuration as well. So while there is a lot to learn, most concepts transfer easily and can be learned once and applied across everything.
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Support Rating
Apache
Support for Apache Kafka (if willing to pay) is available from Confluent that includes the same time that created Kafka at Linkedin so they know this software in and out. Moreover, Apache Kafka is well known and best practices documents and deployment scenarios are easily available for download. For example, from eBay, Linkedin, Uber, and NYTimes.
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Mirantis
The community support for Docker is fantastic. There is almost always an answer for any issue I might encounter day-to-day, either on Stack Overflow, a helpful blog post, or the community Slack workspace. I've never come across a problem that I was unable to solve via some searching around in the community.
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Alternatives Considered
Apache
I used other messaging/queue solutions that are a lot more basic than Confluent Kafka, as well as another solution that is no longer in the market called Xively, which was bought and "buried" by Google. In comparison, these solutions offer way fewer functionalities and respond to other needs.
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Mirantis
We've used XAMPP, PHPmyAdmin and similar local environments (our app is on PHP). Because of how easy you can change the configuration of libraries on PHP and versions (which is SO painful on XAMPP or other friendly LAMP local servers) we are using Docker right now. Also, being sure that the environment is exactly the same makes things easier for developing.
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Return on Investment
Apache
  • Positive: Get a quick and reliable pub/sub model implemented - data across components flows easily.
  • Positive: it's scalable so we can develop small and scale for real-world scenarios
  • Negative: it's easy to get into a confusing situation if you are not experienced yet or something strange has happened (rare, but it does). Troubleshooting such situations can take time and effort.
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Mirantis
  • Docker has made it possible for us to deploy code faster, increasing the productivity of our development teams.
  • Docker has made it possible for us to decentralize our build and release system. This means that teams can deploy on their own schedule and our dev ops team can concentrate on building better tools rather than deploying for the teams
  • Docker has allowed us to virtualize our entire development process and made it much simpler to build out new data centers. This, in turn, is significantly increasing our ROI by providing a path forward for internationalization.
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