In Redpanda, the areas that have room for improvement are in the clustering part. Setting up clustering initially is very easy. However, if you are removing a node and attaching another node, significant improvement is required. It is not as expected, and we have had a tough time adding and removing nodes. Other solutions lack clustering support, but Redpanda has good clustering support, though it needs further improvements for smoother cluster operations. Aside from clustering, Redpanda is good, but it is worth noting that it is built on top of a special architecture. It works directly at the Linux kernel level. Because of that, it needs better modern hardware with a better CPU, not just a normal CPU. A server-grade CPU is required. It also needs modern memory, at least DDR5. It is not good with very old computer memory. Disk type matters as well. It is very good at NVMe SSDs but not good with old spindle hard drives. If a customer has modern hardware, it works very well. If a customer has legacy hardware, it will not work as expected.
Redpanda can be improved by providing more local meetups or online meetups to increase awareness, as very few people know about it. I think Redpanda is overall very good for us, and I am uncertain whether Redpanda can scale to very large companies as we are a medium-sized startup. However, if we consider an example of a very large company like Uber, I am not sure whether it would fit there.
Big Data Teaching Assistant at Center for Cloud Computing and Big Data, PES University
Real User
Top 5
Oct 25, 2024
Recently, for the documentation, they've built their own AI chatbot, which is focused on giving you answers based on their documentation. While using that, I did not find it to be very good. Maybe due to the fact that it's a first prototype and was very recently released. However, from a product perspective, I do not have any problems.
Lead DevOps Engineer at Activelobby Information Systems Pvt Ltd.
Real User
Top 5
Sep 19, 2024
When it comes to self-hosting, their documentation could be improved. At the time we were onboarded, we had to apply our logic. Updating the documentation and managing the automation file for customer users to self-host would be beneficial.
The version control mechanism must be improved. Converting messages takes time. There is a version mechanism in the tool. It follows the coding standard, but sometimes, it gets confusing because I have to remove the older version to ensure the new version works fine.
Redpanda offers a modern, intuitive interface with efficient resource usage, seamlessly integrating with Kafka, and enhancing performance through fast operations and reliable support. Organizations benefit from its memory efficiency and high performance for demanding data workloads.Built on a C++ foundation, Redpanda integrates easily with Kafka clients and stands out for fast operations, simplified Docker setup, and effective metrics monitoring. Performance is enhanced by memory efficiency...
In Redpanda, the areas that have room for improvement are in the clustering part. Setting up clustering initially is very easy. However, if you are removing a node and attaching another node, significant improvement is required. It is not as expected, and we have had a tough time adding and removing nodes. Other solutions lack clustering support, but Redpanda has good clustering support, though it needs further improvements for smoother cluster operations. Aside from clustering, Redpanda is good, but it is worth noting that it is built on top of a special architecture. It works directly at the Linux kernel level. Because of that, it needs better modern hardware with a better CPU, not just a normal CPU. A server-grade CPU is required. It also needs modern memory, at least DDR5. It is not good with very old computer memory. Disk type matters as well. It is very good at NVMe SSDs but not good with old spindle hard drives. If a customer has modern hardware, it works very well. If a customer has legacy hardware, it will not work as expected.
Redpanda can be improved by providing more local meetups or online meetups to increase awareness, as very few people know about it. I think Redpanda is overall very good for us, and I am uncertain whether Redpanda can scale to very large companies as we are a medium-sized startup. However, if we consider an example of a very large company like Uber, I am not sure whether it would fit there.
Recently, for the documentation, they've built their own AI chatbot, which is focused on giving you answers based on their documentation. While using that, I did not find it to be very good. Maybe due to the fact that it's a first prototype and was very recently released. However, from a product perspective, I do not have any problems.
When it comes to self-hosting, their documentation could be improved. At the time we were onboarded, we had to apply our logic. Updating the documentation and managing the automation file for customer users to self-host would be beneficial.
The version control mechanism must be improved. Converting messages takes time. There is a version mechanism in the tool. It follows the coding standard, but sometimes, it gets confusing because I have to remove the older version to ensure the new version works fine.