Aiven Platform vs Google Cloud Dataflow comparison

"One of the most valuable features of Aiven Platform is that it handles the upgrades for us seamlessly, saving us time that would be spent on routine upgrades."

"What I like best about the tool is that the process for the services is faster compared to other methods. It's easier to use because Aiven for Apache Kafka handles the maintenance, so we have less to manage. We only use Kafka to manage its connectivity."

"I don't need a server running all the time while using the tool. It is also easy to setup. The product offers a pay-as-you-go service."

"Google's support team is good at resolving issues, especially with large data."

"The best feature of Google Cloud Dataflow is its practical connectedness."

"The solution allows us to program in any language we desire."

"The most valuable features of Google Cloud Dataflow are the integration, it's very simple if you have the complete stack, which we are using. It is overall very easy to use, user-friendly friendly, and cost-effective if you know how to use it. The solution is very flexible for programmers, if you know how to do scripts or program in Python or any other language, it's extremely easy to use."

"The integration within Google Cloud Platform is very good."

"I would rate the overall solution a ten out of ten."

"It is a scalable solution."

"I would really like to see Aiven Platform add a user interface for database backups, as this would eliminate the need for a third-party solution."

"One challenge we face is when we want to update the version, for example, from 3.6 to 3.7. It will spawn new nodes, and then there's rebalancing and syncing from other brokers. There's high CPU usage during this process, so the solution can't be used for a while, causing some downtime in our services. To tackle this challenge, we schedule maintenance updates during low-traffic periods when there's less risk and fewer users use the services."

"I would like to see improvements in consistency and flexibility for schema design for NoSQL data stored in wide columns."

"Google Cloud Dataflow should include a little cost optimization."

"Occasionally, dealing with a huge volume of data causes failure due to array size."

"The authentication part of the product is an area of concern where improvements are required."

"The system could function in an automated fashion and provide suggestions based on past transactions to achieve better scalability."

"Promoting the technology more broadly would help increase its adoption."

"The technical support has slight room for improvement."

"There are certain challenges regarding the Google Cloud Composer which can be improved."

"The solution is not very expensive."

"The tool is cheap."

"Google Cloud Dataflow is a cheap solution."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a seven to eight out of ten."

"Google Cloud is slightly cheaper than AWS."

"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."

"The solution is cost-effective."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate Google Cloud Dataflow's pricing a four out of ten."