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.
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Mixpanel
Score 8.4 out of 10
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Mixpanel helps companies measure what matters, make decisions fast, and build better products through data. With self-serve product analytics solution, teams can analyze how and why people engage, convert, and retain—in real-time, across devices—to improve their user experience. Mixpanel serves over 26,000 companies from different industries around the world, including Expedia, Uber, Ancestry, DocuSign, and Lemonade. Headquartered in San Francisco, Mixpanel has offices in New York,…
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Pricing
Apache Kafka
Mixpanel
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Free
$0
per month
Growth
$17
per month
Enterprise
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Apache Kafka
Mixpanel
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No
No
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Mixpanel uses MTU (Monthly Tracked User) pricing, which is designed to scale with your company. MTUs are roughly equivalent to the number of unique visitors on your product and each user is counted once per month, even if they use multiple devices. If Events based pricing makes more sense for your business, reach out to us and we can work with you!
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.
As a worker in the sales area, I see closely how complex it can be to evaluate the commercial funnel and Mixpanel has been an indispensable guide to prioritize above all what customers expect to receive from our company, and thus be able to determine the main service we offer. Without a doubt, Mixpanel has special functions to be the one that guides the route and marks the objectives much more clearly.
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).
Mixpanel is a daily use application for everyone in my organization; it helps us have a better flow of information and interaction between work teams.
The user interface of this platform is simple and has a wide variety of functions and resources to help us work in the most organized way, have better team coordination, and keep efficiency high.
I love that it is so easy to program our calendar to our liking, so we can prioritize our activities and know what is pending, and the best thing is that I can update the calendar if necessary.
The chat function is great to improve the interaction between colleagues and share work schedules and any information with third parties.
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
Mixpanel requires an explicit setting of events from your app. This means you need to be very thoughtful in the design of your events because missing one means you aren't collecting any data from it. Inserting it into the process later on then brings challenges in tracking when certain events came online.
A tool like Mixpanel comes packed with features that sometimes are harder to discover. It's very easy to get sucked into one part of its toolset and not be aware of other tools which may be very useful.
It's not an all encompassing solution like Google Analytics tries to be, but MixPanel offers much easier to use and understandable data insights. That's valuable when juggling many responsibilities as startup life demands, so a renewal would be easily justified.
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
Relativity easy to use. Once you get the hang of it, very easy to create dashboards for different use cases. I split my dashboards between customers or use cases
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.
We have only ever had to use their support once, when we were setting up the account, but their responses were prompt and the solutions were well documented. The people who solved our issues were helpful, even to non-tech people.
Mixpanel has a great resource about their product, with videos on how to use it and real world examples from other companies on how they integrate Mixpanel into their business processes.
Again, somewhat annoying to be charged based on data points when many other analytics providers have one flat fee. Implementation was good, but I might have tracked a few more detailed points if I had the option.
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.
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.
We've been able to increase the funnel conversions of one of our new product funnels from a 1% conversion rate to a 5% conversion rate.
We've been able to increase the CTR on another of our main product pages from ~3% to ~10% (so far)
We've been able to segment out how users from different traffic sources behave, allowing us to eliminate thousands of dollars of wasteful spending on advertising campaigns that weren't working.
