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
Jitterbit
Score 7.0 out of 10
N/A
Jitterbit is a cloud integration technology for cloud, social or mobile apps. It provides accessibility for
non-technical users, including easily creating API’s and data transformation scripts within the
integrations.
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.
This is a great tool for bringing data out of your locked, internal systems and getting it into the cloud. It meshes well with Salesforce and is fairly easy to use, helping the transition from other older, more complex tools into a more modern environment. It has lots of competition in this space and some are better than others, but if your data is straight forward and you know it well, Jitterbit will get the job done. If you are not as close or comfortable with your data and need to do some wildly complex migrations, there might be better packages out there for you.
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
Migrating operations from QA to Production work well for initial deployment, however, when migrating an update to an existing job to production, sometimes certain project items are duplicated. This is not the end of the world... the duplicates can be removed, but would be nice if it was not required.
I have not found a way to trap under-the-covers SOAP errors (for example, when a query you are running against Salesforce takes too long). You get a warning error in the operation log that the job only pulled a "partial" file, but it does not fail.
I have been evaluating other tools as a continuous improvement practice. I would like something that would be easier to use for a non-technical user. I work for a small organization and have no back-up for Jitterbit if something happens to me. We don't have the technically savvy employees to understand it.
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
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.
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.
Evaluated Dell Boomi and Celigo as alternatives prior to purchasing Jitterbit. We went with Jitterbit at that time because we could handle all changes ourselves without any assistance from Jitterbit, and we liked their size and nimbleness. Dell Boomi was too big for us, and Celigo at that time did not have a self-service model. Every change had to go through them (although that has since changed). We were not in a position to be able to wait for someone to make changes for us given the rate of change within the business.
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.
The time it takes to connect systems has reduced by orders of magnitude. Previously, we would custom-develop connectors between various systems and they would all be managed by different vendors. With Jitterbit speed-to-deploy and the efficiency gained by managing all connections in one dashboard has been the greatest piece of the ROI.
