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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IBM Aspera on Cloud
Score 8.8 out of 10
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IBM Aspera on Cloud is an on-demand SaaS offering for global content transfer and exchange. It enables organizations to move large files and data sets securely and reliably across on-premises and multi-cloud environments at high speed. With Aspera on Cloud, organizations can store and access files and folders across multiple cloud-based and on-premises storage systems. Sharing among users is as simple as browsing or drag-and-drop — no matter where the files are stored — making…
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.
In one specific situation I had to quickly transfer about ten files really fast that were really large but my colleague from another company only had Aspera and it worked so well with no errors and was so fast. It was really helpful to get our promo done with our strict deadline.
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
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
My experience with Aspera applications and with other vendors. My score will go to 8 as soon as AoC's Files App has the Search Through Sub-folders feature. We want to remove Aspera Shares, which has an older inefficient user interface.
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 from IBM is fast and reliable. Very knowledgeable engineers provide you with the support on Aspera. We had a very good experience when opened tickets and we were able to get our issues resolved quickly. Most solutions are provided within a day so you can expect a quick turnaround time. Overall, the support has been very good.
The service provided by the authorized vendor was excellent. It was a good collaboration between the vendor IT team and internal IT team. They provided us with a timeline and we verified and approved that timeline. Daily stand ups and weekly meetups were conducted to update the internal team on progress. They were able to deliver all deliverables on time also, they conducted both alpha testing and beta version testing in time. Overall, they were able to complete the implementation in the given timeline.
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.
These cloud storage products deliver sufficient space to store data and access and have an array of ways to transfer this data and keep it secure. IBM Aspera on Cloud focuses on the transfer and makes it a lot faster mainly due to its patented tech and altered UDP protocol. Since most of production code uses IBM services, it was natural to go with IBM Aspera on Cloud.
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.
