Likelihood to Recommend 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.
Read full review APIM is useful for the standard scenarios:
1) Securing your back-end APIs - If you have a legacy back-end web service that has a basic authentication scheme, you can add some additional security by placing APIM in front, and requiring subscription keys. Leverage your existing firewall to ensure only your APIM instance can communicate with your back-end API, and you've basically added a layer of protection.
2) Lift and shift - there are always going to be clients that don't want to update their clients to use a newer API; in some cases you can make a newer API look like an older one by implementing some complex policies in APIM. You can also do the opposite, making older APIs look new, such as making an XML back-end accept both JSON and XML.
3) Centralizing your APIs - if you've acquired another company and want to make their API set look as if it's a part of the larger whole, APIM is an easy way to provide a consistent front-end interface for developers.
Read full review Pros 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). Read full review Easy commissioning of APIs. Great policies to control access. Easy mock services for testing. Read full review Cons 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 Read full review Lack of robustness is a bit of an issue. Several other providers offer more options and capabilities, but then, they are lacking in interface ease. As with anything Azure, pricing is really hard to stay on top of. I always find that you really don’t know what you’re paying for until you get the bill. Having an excellent Azure Administrator can help resolve that. Integrating with app services outside of Azure can be a challenge, or at least much more challenging than just using Azure App Services. Read full review Likelihood to Renew Kafka is quickly becoming core product of the organization, indeed it is replacing older messaging systems. No better alternatives found yet
Read full review Usability 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
Read full review Support Rating 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.
Read full review Alternatives Considered 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.
Read full review Azure APIM vs
Amazon API Gateway :
1) Azure APIM was a complete package that included a developer portal.
2) We are very Microsoft centric - so the Microsoft product suite aligned very well with our business needs.
3) It was faster and easier to stand up Azure APIM for testing than it was for the
Amazon API Gateway .
Read full review Return on Investment 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. Read full review We can always think of positive ROI impact on business It helps to easily facilitate the design, deployment, and maintenance of our APIs Read full review ScreenShots