Apache Flink Reviews and Pricing

Ertugrul Akbas

Manager at ANET

Jan 30, 2023

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Easy to use, stable, scalable, and has good community support with a lot of documentation

Pros and Cons

"It is user-friendly and the reporting is good."

"There is a learning curve. It takes time to learn."

What is our primary use case?

We use Apache Flink in-house to develop the Tectonic platform.

What is most valuable?

It's usable and affordable.

It is user-friendly and the reporting is good.

What needs improvement?

There is a learning curve. It takes time to learn.

The initial setup is complex, it could be simplified.

For how long have I used the solution?

I have been using Apache Flink for more than one year.

I am using the latest version.

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What do I think about the stability of the solution?

Apache Flink is a scalable product. We have no issues with the stability.

What do I think about the scalability of the solution?

It's a very scalable solution. We have more than 100 people in our organization who are using it.

How are customer service and support?

We use community resources. There is a lot of documentation available online.

How was the initial setup?

The initial setup is complex.

What's my experience with pricing, setup cost, and licensing?

It's an open-source solution.

Which other solutions did I evaluate?

We have not evaluated competitors. We followed the trends and based on the experience and opinions of people from all over the world, we selected Apache Flink.

What other advice do I have?

I would recommend Apache Flink to others who are interested in using it.

I would rate this solution an eight out of ten.

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.

reviewer1494531

Head of Data Science at a energy/utilities company with 10,001+ employees

Feb 7, 2021

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Easy deployment and install, open-source, but underdeveloped API

Pros and Cons

"The setup was not too difficult."

"In a future release, they could improve on making the error descriptions more clear."

What is our primary use case?

I use the solution for detection of streaming data.

What needs improvement?

I am using the Python API and I have found the solution to be underdeveloped compared to others. There needs to be better integration with notebooks to allow for more practical development. Additionally, there are no managed services. For example, on Azure, you would have to set everything up yourself.

In a future release, they could improve on making the error descriptions more clear.

For how long have I used the solution?

I have been using the solution for two weeks.

Which solution did I use previously and why did I switch?

I have used many different competing solutions in the past such as Pyspark, Hadoop and Storm.

How was the initial setup?

The setup was not too difficult.

What about the implementation team?

To deploy the solution locally it was relatively easy.

What's my experience with pricing, setup cost, and licensing?

The solution is open-source, which is free.

What other advice do I have?

When choosing this solution you have to look at your use case to see if this is the best choice for you. If you need to have super-fast realtime streaming, and you can develop in Scala, then it might make a lot of sense to use it. If you are looking at delays of seconds, and you are working on Python, then Pyspark might be a better solution.

I rate Apache Flink a six out of ten.

Disclosure: My company does not have a business relationship with this vendor other than being a customer.