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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Oracle Integration (OIC)
Score 5.0 out of 10
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The Oracle Integration Cloud Service is an iPaaS providing prebuilt integration flows between applications, including other Oracle products. The Integration Cloud Service is scaled for enterprises, with prebuilt codeless adapters for on-premises and SaaS systems and low-code automation capabilities.
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.
For all type of integration except those with a huge volume. It can deal with 20MB of transactions and processing of 1GB file when a file is being read using file or FTP adapters. It cannot be used for EDI as this support is not there. OICS is a perfect fit for other integration and is best when a customer has Oracle applications in the landscape. It is even greater if you have a requirement to create a custom form and make use of Process Cloud. All of these work very well together seamlessly. API needs can be handled by APIary.
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).
Auto-association of Oracle applications prepopulates the application connector select box and preconfigures Oracle Integration (OIC) using secure credential access for faster integration.
Various other system connectors are available to use readily.
User-intuitive experience--Connectors, integrators, and dashboard can be seen on one page.
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
Currently, it is not retaining the logs for more than 3 days, which it needs to address.
We also need some functionality inside the interface to re-push the same transaction again so that it will be helpful while testing and fixing the issue.
Also, some log errors are not giving the correct details. Oracle needs to rectify those.
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.
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.
The nearest thing I have used to OIC is UiPath, as it is often used as a tool to integrate software together. However, it is much more suited to legacy software which have little to no API endpoints. If the infrastructure already exists I understand why people use RPA for integration, however for when API's are easily accessible and you're using Oracle tools, OIC is better.
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.
Created a solution for unique business integration with minimal processing times
Saves my team about 7 hours per week because of how it communicates with all the information. Because it communicates faster, and because there's a lot of information to communicate with, another solution might not work.
