We use the solution for analytics for streaming. We also use it for fraud detection.
Building Event-centric Data processing Architectures at a tech services company with 51-200 employees
The product is scalable and provides good connectors, but the ability to connect the producers and consumers must be improved
Pros and Cons
- "The connectors provided by the solution are valuable."
- "The ability to connect the producers and consumers must be improved."
What is our primary use case?
What is most valuable?
The Kafka Streams library gives quite a bit of functionality. The connectors provided by the solution are valuable.
What needs improvement?
The ability to connect the producers and consumers must be improved. It's still a pain point because a lot of development goes into it.
For how long have I used the solution?
I have been using the solution for seven to eight years.
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What do I think about the stability of the solution?
For what it does, the tool is very stable. It is a message broker. It receives the messages and holds them for producers and consumers. It's usually everything around Kafka that has stability problems because Kafka does exactly what it's supposed to do.
What do I think about the scalability of the solution?
Scalability is one of the main selling points of the tool. The additional nodes we add give us the additional storage capacity we need. I rate the scalability a ten out of ten. The solution is used across multiple domains in our organization. I use the product daily. It’s a continuously growing platform.
How are customer service and support?
Apache doesn't provide support. There are sites we can go to for information, but there's no support team for Apache. There are companies like Confluent and HPE that provide support for the solution.
Which solution did I use previously and why did I switch?
We also use Flink and other streaming tools. We use Apache Kafka in addition to other technologies because of the requirement and the business use cases.
How was the initial setup?
It is super easy to set up. I rate the ease of setup a ten out of ten. However, building and administration get quite difficult. It takes three months to make things production-ready.
What about the implementation team?
The deployment was done in-house. We used the tools that we have in our CI/CD pipeline. We needed three people for the deployment. The infrastructure team maintains the tool. The infrastructure team has three to ten members.
What was our ROI?
We see an ROI on the product. If we don't have a tool to buffer the amount of traffic coming in from high-traffic sites, we cannot use the data. Apache Kafka gives us a resting area where we can push as much information as we want to. It’s picked up by consumers when they need it.
It’s a huge return on investment. Otherwise, we must have a system tied to the producer waiting for the consumer to consume before we can do anything with the rest of the messages. A solution like Kafka provides us with a buffer to consume the data as we choose to.
What's my experience with pricing, setup cost, and licensing?
The price depends on who we are getting the product from. If we buy it from Confluent, we always have to try to negotiate the price. The price is always negotiable.
What other advice do I have?
Overall, I rate the product a six out of ten.
Which deployment model are you using for this solution?
Hybrid Cloud
Disclosure: My company does not have a business relationship with this vendor other than being a customer.
Freelance at a tech services company with 11-50 employees
The solution is flexible, stable, reliable, and robust
Pros and Cons
- "I like Kafka's flexibility, stability, reliability, and robustness."
- "Kafka has a lot of monitors, but sometimes it's most important to just have a simple monitor."
What is most valuable?
I like Kafka's flexibility, stability, reliability, and robustness.
What needs improvement?
Kafka has a lot of monitors, but sometimes it's most important to just have a simple monitor. Improvements to Kafka's management would be nice, but it's not so necessary for me. There are a lot of consoles that offer a better view than Kafka. Some are free, and some are paid, but I'm thinking about streaming. For example, if you connect more streams to a component in the same queue, how will it integrate to recognize the flow and the message?
For how long have I used the solution?
I've been using Kafka for more than two years.
What do I think about the scalability of the solution?
Kafka is stable. Defining our user base is hard because Kafka influences the whole company, so you could say around 100 users. Kafka is a core system, so it affects all users we choose to link to the primary key.
Which solution did I use previously and why did I switch?
I previously used IBM MQ.
How was the initial setup?
The first time we tried to deploy Kafka, it seemed a little complicated, but the second try went better. Sometimes it isn't easy to set up the necessary communication or estimate how many partitions we need. Some applications have a vast amount of data, so we have to consider how to improve the performance and not increase the transfer times.
What other advice do I have?
I rate Apache Kafka nine out of 10. I think it's one of the best tools on the internet.
Which deployment model are you using for this solution?
On-premises
Disclosure: My company does not have a business relationship with this vendor other than being a customer.
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