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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Boomi
Score 7.9 out of 10
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Boomi is a cloud-based, on-premise, or hybrid integration platform. It offers a low-code/no-code
interface with the capacity for API and EDI connections for integrating with external organizations and
systems, as well as compliance with data protection regulations.
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.
Legacy systems often need to be replaced or integrated with new applications in order to modernize businesses. A strong API strategy that avoids custom coding and third-party programs is essential to enable this integration. Boomi's new-age connectivity and integration solutions ensure safe, secure, and robust integration. In the age of information, businesses are under more pressure than ever to be able to collect and manage large amounts of data. This data comes in from a variety of sources, including personalized devices such as voice assistants and wearable tech. While this data can be immensely valuable to businesses, they often lack the infrastructure necessary to handle it effectively. This can lead to data build-up in databases or silos, and can eventually lead to problems with integration and security.
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
More from a development perspective. It is always difficult to use the properties features. It takes a while to understand how the data/variables can be used across an integration.
Dell Boomi should also invest more on API Management and not just seen as a ETL,ESB tool.
Should roll out features more often based on users reviews.
Dell Boomi has provided us with the ability to connect our campus together using our various existing platforms. There are many supported features and have yet to run into something that we cannot do. Its user interface is very intuitive which would allow users to begin developing fairly easily. There is a myriad of resources available
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 IT and Finance teams have noted that setting up the tool is a breeze. Dell Boomi has never caused an issue during a system implementation that I am aware of. We are pleased with the tool and recommend others consider it.
The atom sphere takes a time to load, when I open a process or when I open a log. One more slow processing is when I import objects from NetSuite.
About the performance of processing, it looks like Boomi takes a time to initialize some things such as connectors before starting the process. This is also performance we have.
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.
Boomi support was responsive and knowledgable, however being a closed cloud service, it doesn't have good community support. We found the learning curve to be steep and there aren't avenues like google, forums, or blogs that provide community driven insight into the product or how to go about designing solutions using the tool
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.
We decided to go with Dell Boomi because another department in our company was already using the software. We did not research competitor applications to use as our business solution. Dell Boomi was very easy and quick to set up, so once we decided to use Dell Boomi for systems integration, we had it set up and running within a few working days.
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.
It has allowed us to scale significantly without having to add headcount, specifically those geared towards data entry. We went from a $10m ARR business to $200m ARR business with the same amount of Order Processors and 12x amount of transactions by leveraging Boomi to perform a lot of the work, and then having the Order Processing team to simply review that the transaction was processed successfully.
