Amplitude Analytics is an analytics platform for mobile and web. It is designed to help organizations segment users and analyze funnels,
retention and revenue. Amplitude Analytics helps you achieve actionable insights from customer digital journeys and uses behavioral graphs to build customer-focused products. Amplitude also optimizes digital products for increased quality engagements, increased conversion rates, and long-term customer loyalty.
$59
per month
Apache Kafka
Score 8.2 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.
Amplitude Analytics is an excellent solution for anyone with a mobile app and you want to track what users are doing, are they completing conversion steps, and are they coming back more often. This all helps you visual your customer bases engagement and help project future engagement and create goals. This also helps with prioritizing products to address drop-off points in the product to increase conversions.
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.
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).
Some offerings seem duplicative, like dashboards and notebooks, which only seem to differ in that one can subscribe to dashboards
The messaging on valid vs invalid property types could be better explained to clarify which types (string, Boolean, integer, etc) are expected in particular scenarios. Though the type is usually set during event creation, we've often seen examples where the data received in production is different, leading to 'invalid type' errors
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
Great product Good value for the cost/initiate Support docs and FAQs are great - they limit the necessity of reaching out to in-person support. So when you do call them ... it is for a legit question/issue, no just a "where is it" or a "how to I do xyz123?"
It's a fairly straightforward platform that's beginner friendly. The biggest usability hurdle is most often created by your own team, as it's imperative to know what event sources are being sent to Amplitude and what those event names are. Within being properly onboarded by a team member it can be hard to get started using Amplitude. It takes time to understand what data your company may be sending to the product, the naming conventions of events (especially if there are old or deprecated events names
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
Alway up and running, or if there is a problem we can get back in the game right away. The reliability was a big selling point for me, and it was true when this company got it. Rollouts can be tough, but this was pretty seamless. Good support throughout the process, good documentation to handle questions/tips
No issues, problems, or negative remarks from us!! We had a plan, vendor support was rock solid, our data folks have experience, OCM supported as needed, and we got the rollout done on time, on budget, and with only minor hiccups. SInce the rollout, most of us have already forgotten the hiccups and generally speak highly of the product
I haven't used the Amplitude support other than their training docs so I can't speak too much to the in-person support but the docs are serviceable. Nothing too crazy but between the user tips, email notifications, and the decent number of docs I was able to get the support I needed to ramp up on the tool.
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.
Virtual Not bad considering the timeframe and turnaround. The biggest benefit was for my end-users to hear a voice (other than mine/ours! LOL) telling them about the new features and capabilities. The in-person training was really good for having an expert that knows the answers and could refer to past experiences, problems, solutions. THey were a great resource to ease the transition ... basically a "you are gonna be okay with this change ... you got this etc.!" kinda vibe
Good enough to get strong baseline. I always make sure our our users go to and/or focus on the vebndor-provided support docs rather than any formal training. Our instructors come and go, but written policy and how-to docs live much longer in a corporate setting. That said, the online training is sufficient. I like that the training curric is stacked and progressive.
My team members all have background as data analysts, so Amp was pretty easy to for them. There was sufficient online training available. We also used the available support documents. The actual rollout went well. We did significant testing beforehand. We did a phased rollout, with partial silent rollout (part of OCM's plan) for the smallest line of business. THe silent one was "silent" b/c it was done without fanfare or public notices ... it was just a "we're doing some things, it wont impact your work or workday
Amplitude Analytics provides much more granular data than Google Analytics and gives you much more flexibility in how you can segment and splice the data. It also provides the ability to create closed funnels, which I have yet to find out how to do in Google Analytics. Amplitude has a very similar interface to Mixpanel, with a few handy additions, like the ability to name and categorize your events.
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.
Like all the other grades, it was mostly an easy implementation ... we have experience people, the rollout in general is well planned, and the vendor was very supportive
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.