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 HANA Cloud
Score 9.0 out of 10
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SAP HANA is an application that uses in-memory database technology to process very large amounts of real-time data from relational databases, both SAP and non-SAP, in a very short time. The in-memory computing engine allows HANA to process data stored in RAM as opposed to reading it from a disk which means that the data can be accessed in real time by the applications using HANA. The product is sold both as an appliance and as a cloud-based software solution.
As discussed earlier, SAP HANA is one of its kind. With SAP HANA, we are much better equipped to handle and go even beyond the big data trend. Its machine learning and advanced analytic capabilities allow us to integrate with many external and internal resources. [Another] …
We compared Microsoft BI with SAP HANA. The reasons to go with SAP HANA were - 1. ability to ingest data into HANA from a non SAP database 2. in-memory database resulting in faster real time analytics 3. ability to scale up 4. ability to replicate data real time 5. very solid …
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.
I think if you have a large organization, it's probably the product and the marketplace to go to. We're a large management consulting firm operating in four to seven countries. And generally speaking, I think that's the size and the scope where it scales best. I can't speak to smaller companies, but I can't see smaller companies leveraging the benefits as much as a larger organization can.
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).
Real-time reporting and analytics on data: because of its in-memory architecture, it is perfect for businesses that need to make quick decisions based on current information.
Managing workload with complex data: it can handle a vast range of data types, including relational, documental, geospatial, graph, vector, and time series data.
Developing and deploying intelligent data applications: it provides various tools for such applications and can be used for machine learning and artificial intelligence to automate tasks, gain insights from data, and make predictions.
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
Requires higher processing power, otherwise it won't fly. How ever computing costs are lower. Incase you are migrating to cloud please do not select the highest config available in that series . Upgrading it later against a reserved instance can cost you dearly with a series change
Lack of clarity on licensing is one major challenge
Unless S/4 with additional features are enabled mere migration HANA DB is not a rewarding journey. Power is in S/4
We would rate our likelihood of renewing at 9/10. SAP HANA Cloud has proven to be a highly reliable and scalable data platform that consistently delivers strong performance. Its seamless integration with our overall SAP landscape, combined with improved analytics and real-time data capabilities, makes it a core part of our long-term technology strategy.
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
It is very useful solution which provides you speedier data processing, real-time analytics. It helps you manage diverse data types. It also offers you excellent disaster management. It has user friendly interface which helps you navigate system and transactions easily and perform task smoothly.
I would rate SAP HANA Cloud’s availability as an 8 out of 10. In general, the platform is available when we need it and provides a reliable cloud environment for our data, reporting, and integration use cases.We have not experienced availability as one of the main issues compared with areas like configuration, troubleshooting, or support response quality. However, I would not rate it a 10 because, like any cloud platform, availability can still be affected by occasional service issues, application errors, maintenance windows, or dependencies with connected systems.Overall, SAP HANA Cloud has been reliable for our needs, but continuous monitoring and clear communication around incidents or maintenance are still important.
I would rate SAP HANA Cloud’s performance as an 8 out of 10. In general, performance is strong and reports usually complete in a reasonable time frame, especially when the data models, queries, and calculation views are well designed.The platform handles large data volumes well and supports fast analytics for many enterprise scenarios. It also works effectively with connected systems when the integrations are properly configured.I would not rate it a 10 because performance can depend heavily on architecture, query design, data volume, custom code, and integration complexity. In some cases, complex reports, large datasets, or custom logic require additional tuning and testing to avoid slow response times or delays in connected processes.
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.
However, I am not the right person to answer this as we have another department to handle support and contact the service provider for any support required. Although i will say that they are the quick respondent and knows how to handle querry of the customers and provide quick and better support.
I would rate the online training as an 8 out of 10. The training materials are generally useful, well-structured, and helpful for understanding the main capabilities of SAP HANA Cloud, including data modeling, administration, integration, and analytics.The content is especially valuable for building a foundation and learning the standard features of the platform. However, I would not rate it a 10 because some advanced or real-world scenarios, such as complex integrations, troubleshooting, performance tuning, and custom code, could benefit from more practical examples and deeper technical guidance.Overall, the online training is strong, but it could be improved with more hands-on exercises and more examples based on enterprise implementation scenarios.
would rate our satisfaction with the implementation as a 6 out of 10. The implementation was completed and the solution provides value, but the process was more complex and time-consuming than expected.The main challenges were related to technical configuration, integrations, permissions, and troubleshooting. In some cases, getting clear answers or resolving issues required several iterations, which slowed down the implementation.Overall, the final result is useful, but the implementation experience could have been better with clearer documentation, more straightforward configuration steps, and more effective support during the process.
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.
I have deep knowledge of other disk based DBMSs. They are venerable technology, but the attempts to extend them to current architectures belie the fact they are built on 40 year old technology. There are some good columnar in-memory databases but they lack the completeness of capability present in the HANA platform.
I would rate the contract terms and pricing structure for SAP HANA Cloud as a 7 out of 10. Overall, the pricing model is reasonable for an enterprise cloud platform, especially considering the scalability, integration capabilities, and performance benefits it provides.However, there are some aspects we would improve. The pricing model could be more transparent and easier to predict, especially when usage grows across multiple departments, data volumes increase, or additional capacity is required. It would also be helpful to have clearer guidance on how configuration, storage, compute, and scaling decisions affect overall cost.If we could change anything, we would prefer simpler pricing, more predictable billing, and more flexibility to adjust capacity without creating unexpected cost increases.
I would rate SAP HANA Cloud’s overall scalability as an 8 out of 10. The product provides strong scalability for enterprise scenarios, especially when it needs to support multiple departments, growing data volumes, and more complex analytics or integration requirements.The cloud-based architecture makes it easier to expand capacity compared with traditional on-premise environments, and it gives the organization flexibility as usage increases across different teams or locations.I would not rate it a 10 because scalability still depends heavily on good architecture, correct configuration, performance tuning, and cost control. As the environment grows, it is important to monitor resource consumption, optimize queries and data models, and make sure the solution is designed properly to avoid performance or cost issues.
I would rate the professional services for SAP HANA Cloud as a 6 out of 10. The professional services were helpful in moving the implementation forward and provided useful knowledge around the platform, configuration, and technical setup.However, the experience was not perfect. Some areas, such as complex integrations, custom code, permissions, performance tuning, and troubleshooting, required more effort and follow-up than expected. In some cases, we would have benefited from clearer guidance, more practical recommendations, and faster resolution of technical questions.Overall, the professional services added value, but there is room for improvement in terms of proactivity, hands-on support, and helping customers handle complex real-world implementation scenarios.
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.
