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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Apigee Edge
Score 7.7 out of 10
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Apigee Edge is an API management platform now owned and offered by Google, since Google acquired Apigee in 2016.
Apigee is the best in the market in terms of API Analytics Apigee is having wonderful Documentation with short videos Security is a major concern and Apigee provides an easily configurable policy to secure API Quota and rate-limit is again very easy to configure on every API …
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.
Few scenarios 1. For viewing API analytics, I think it is best in the market 2. For earning money via API monetization 3. Securing API 4. Onboarding legacy APIs to provide modern REST endpoints
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).
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
Prohibited from using JSON.stringify on Apigee objects (tokens)
Debugging is difficult
Unable to rename or delete policies without bumping revision
Why would anyone give a js policy one name, display name something else, and script a different name?
'Trace' limited to only 20 transactions
UI allows users to add target servers, but users must utilize the api to turn on SSL.
I'm sure there's more, they just aren't coming to mind right now.
Apigee forgets (expires?) your password at random intervals without notice. Every few weeks, or days, sometimes even three times in one day, I'll attempt to login to Apigee and my password will be 'wrong'. I've reset my password and Apigee still claims it's wrong. I've had to reset my password three times before it finally let me log back in.
I am not the one deciding whether to use apigee or not really. But personally, I would recommend the use of it as developing APIs on it is easy. And as a mediator between backend servers, we could easily modify request and responses in it without touching any backend code while having a centralize gateway to access our backend APIs too.
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
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.
Quite hard to get support, at least on the coding side, when we encounter blockers. But general concerns, they would schedule a call to you for them to get a whole picture of your concern. Albeit in my experience, bad really as they haven't replied about the progress, but otherwise seems to have been fixed.
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.
Apigee is the best in the market in terms of API Analytics Apigee is having wonderful Documentation with short videos Security is a major concern and Apigee provides an easily configurable policy to secure API Quota and rate-limit is again very easy to configure on every API basis It provides various policies to transform the response from one form to another form e.g. JSON to XML or XML to JSON
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.
As a public entity it is hard to say how much ROI we can have. We have yet to create a billing and ROI plan. We are thinking of other ways to create ROI, possibly through data/service barter.
