Apache Kafka on Confluent Cloud enables organizations to perform real-time data streaming and processing, integrating user data, and managing large transaction volumes efficiently.
| Title | Rating | Mindshare | Recommending | |
|---|---|---|---|---|
| Security Onion | 3.8 | 1.3% | 66% | 3 interviewsAdd to research |
| Cloud Security Connector for Zscaler | 4.5 | 0.8% | 100% | 2 interviewsAdd to research |
Organizations leverage Apache Kafka on Confluent Cloud for several applications such as capturing change data, handling IoT workloads, and fostering data migration and microservices. It is instrumental in publishing and managing data across multiple platforms, ensuring both high throughput and seamless log management. Confluent Cloud's features like scalability, efficient transaction management, and cost-effectiveness, combined with seamless integration with multiple data tools, make it a preferred choice for real-time data processing tasks.
What are the key features?
What benefits and ROI should you look for?
In specific industries, such as finance, real-time data processing is crucial for handling high volumes of transactions and location tracking. In retail, it integrates user data and manages inventory systems efficiently. IoT applications benefit from Apache Kafka on Confluent Cloud by capturing and processing massive data streams from connected devices in real-time.
In my company, we are not using the tool for analytics and it is more for CDC processes, so we change the capture processes. It is used to extract data from a database and make it available in other parts of our systems or produce events that inform us of data updates.
There are some premium connectors, for example, available in Confluent, which you cannot access in the marketplace, so there are some limitations. From Confluent's point of view, I understand where they come from, but I believe its deployment model is a little strict. Confluent Platform can be installed in your own infrastructure. Even if you install Confluent Platform on your own platform, you need to use the components that Confluent offers. Otherwise, the support is very limited, and I think this is an idea of improvement for Confluent. Confluent is pretty solid, so I don't have much in terms of improvement.
I have experience with Apache Kafka on Confluent Cloud.
Confluent gives you 99.99 percent availability, so I rate the tool's stability a nine out of ten.
If you use Confluent Cloud, the platform's case can go up and down depending on your needs, and it is very easy from the point of view of storage as well because if you are getting more advanced, it basically scales up your storage. If you are given a number of events using your storage device, it is very easy. If you use Confluent Platform, you have a little bit more manual management there, although being a product that assists you with some side components like CFK.
With Confluent, if you have its tools, I rate the support an eight out of ten, but if you have mixed products, then it is a six out of ten.
Neutral
I have experience with Confluent Cloud and Amazon MSK. With Confluent Cloud, we are really happy with the ecosystem that is made available, along with the connectors, SQL, DB, and other such aspects. The tool can be provided in a very easy way, and it was really effective for the type of activities that we do. The tool presents quite a range of possibilities for integration between different sources and things.
While you use Confluent, all of the services that are needed to manage the enterprise-level EDA are available to you, and you have an integrated schema registry, together with the entire schema registry, and you have a portal for publishing your schema. You can do routing and filtering by configuration. You have CFK, which allows management of your cluster, allows monitoring of your cluster, and allows you basically to connect to the managed connectors on your cluster. Confluent is a full-fledged platform for an event-driven architecture that can be deployed at an enterprise scale, while Amazon MSK is just Kafka as a service from AWS.
A part of the delivery team does the setup, but it was pretty easy on both sides, as with AWS and Confluent, the team didn't have much trouble.
The main return on investment was in the maintenance space because going for Confluent Cloud means you remove all the platform management that you have in terms of these resources that can be allocated to other tasks, where the tool takes basically ownership of all of these. We saw, at the end of the year's end, improvements that were substantial, especially when it comes to the need to resolve issues, as we can deploy the minimum team possible for Confluent because the support model allows for the Confluent team to take ownership of the issue. With AWS, the tool's team supports us, but we have to deploy the right people and take them out of all other initiatives. The most important part is the cost related to platform maintenance and issue resolution.
Using Confluent, you have more licensing prices to account for when you calculate. I think the pricing is fair, but Confluent requires a little bit more thinking because the price can go up really quickly when it comes to premium connectors.
Speaking about data security and privacy requirements, I would say that there are some BAA or legal agreements in the tool. We did not have issues in terms of security or breaches, but before any adoption, with PII or PHI type of data and before having this data flowing to other clouds or other platforms, the BAA needs to be signed because of IPAC.
Confluent Cloud handles data volume pretty well.
If you are starting to deploy a fully-fledged ETA platform where you do not just have information streaming and go for CDC, and you have some legacy systems that have to communicate on your systems, then I suggest you go for Confluent Cloud.
I rate the tool an eight out of ten.
