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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SAP Cloud ERP
Score 8.6 out of 10
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SAP Cloud ERP (SAP S/4HANA Cloud) is a modular ERP that enables users to run mission-critical operations in real time from anywhere, introduce new business models in any industry, and expand globally. SAP Cloud ERP is a SaaS product and can also be deployed in a hybrid landscape for quicker time to value. SAP Cloud ERP is a foundational component of the
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.
SAP Cloud ERP reduces dependency on multiple systems and ensures improved efficiency in enterprise resource planning. Real-time reporting capabilities and scalability of the product. Use of the software ensures compliance and allows smooth integration with other systems. The software allows customization to accommodate users' uniqueness and has very convenient customer support services. The only major challenge with the software is limited configuration.
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
The cost of SAP as an ERP is quite high and the switching costs associated with ERP systems are even higher. That being said moving from one ERP to another only happens once in a great while for large organizations. Those switching costs include retraining, IT hardware requirements, outside consultants and more
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
The software is user-friendly and intuitive. It has extensive and reliable reporting and forecasting systems. Smooth integration of the software with other products and unlimited customization. SAP Cloud ERP software supports many languages and ensures high accuracy in billing and invoicing.
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.
The support system I find great as whenever I run into problems they rectify them quickly as possible they never reacted late the support is just up to the mark for me. They provide many solutions to the problems I faced the [technical] team support is always amazing they [listen] to mean work accordingly.
SAP requires a lot of internal and external resources to complete its successful implementation. The cloud version requires a deeper understanding of the different capabilities of the local systems (hardware) and the connection towards your local IT team. We found several problems on our systems that we couldn't foresee before the implementation and roll out.
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 platform utilizes advanced predictive analytics to anticipate operational bottlenecks and put them out of commission before the problems become larger. We can proactively develop effective strategies that help keep service quality in the face of unexpected changes in the market, or external disruptions, by continuously analyzing historical performance data as well as elements of the current market
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.
