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.
N/A
IBM Aspera on Cloud
Score 9.2 out of 10
N/A
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.
IBM Aspera on Cloud is a great tool for the ones who are looking for a tool which can transfer large datasets, backups, raw files etc., quickly. I think that it is well suited where data transfer at high speed is required and reliability is important. However, it can be less useful for smaller files or data transfer as it can be done with basic tools.
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).
Unlike many others , IBM Aspera on Cloud has the ability to transfer large files even upto 100s of GB really quick . The transfers that used to take 5-6 hours or even sometimes failed after waiting that much of time with IMB same files only take like 30 minutes even over long distances .
Not only it transfers data fast , but IBM Aspera on Cloud on cloud also handles inturrpted transfers well even in case of disconnection or bad connection , the platform automatically resumes from where it got paused saving us a lot of time in starting over . This is huge advantage for large files for example when shifting database exports or large technical confirguration bundles from a remote office with bad connection , IBM Aspera on Cloud resumes automatically and dont have to start it over .
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
1) It works. 2) Is is secure 3) It is fast It provides firms the ability to communicate with vendors other clients and new clients in a way that will help you grow your business. In our business, flies are getting larger larger and can hold companies back in their overall business goals.
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 interface is very pleasing and so easy to use. I have never used a program that was so simple and so effective. Other programs have too many unnecessary features and make everything really daunting and then you just go elsewhere. IBM Aspera is perfect for easy transfers with minimal features.
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.
It is an outstanding product. It is proven and works well. IBM has thought of everything as the product works well and it can scale. I highly recomend this product.
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.
