tiered-storage-for-apache-kafk VS tiered-storage-for-apache-kafka

I am the founder of RisingWave (http://risingwave.com/), an open-source SQL streaming database. I am happy to see the launch of Warpstream! I just reviewed the project and here's my personal opinion:

* Apache Kafka is undoubtedly the leading product in the streaming platform space. It offers a simple yet effective API that has become the golden standard. All streaming/messaging vendors need to adhere to Kafka protocol.

* The original Kafka only used local storage to store data, which can be extremely expensive if the data volume is large. That's why many people are advocating for the development of Kafka Tiered Storage (KIP-405: https://cwiki.apache.org/confluence/display/KAFKA/KIP-405%3A...). To my best knowledge, there are at least five vendors selling Kafka or Kafka-compatible products with tiered storage support:

-- Confluent, which builds Kora, the 10X Kafka engine: https://www.confluent.io/10x-apache-kafka/;

-- Aiven, the open-source tiered storage Kafka (source code: https://github.com/Aiven-Open/tiered-storage-for-apache-kafk...

-- Redpanda Data, which cuts your TCO by 6X (https://redpanda.com/platform-tco);

-- DataStax, which commercializes Apache Pulsar (https://pulsar.apache.org/);

-- StreamNative, which commercializes Apache Pulsar (https://pulsar.apache.org/).

* WarpStream claims to be "built directly on top of S3," which I believe is a very aggressive approach that has the potential to drastically reduce costs, even compared to tiered storage. The potential tradeoff is system performance, especially in terms of latency. As new technology, WarpStream brings novelty, and definitely it also needs to convince users that the service is robust and reliable.

* BYOC (Bring Your Own Cloud) is becoming the default option. Most of the vendors listed above offer BYOC, where data is stored in customers' cloud accounts, addressing concerns about data privacy and security.

I believe WarpStream is new technology to this market, and and would encourage the team to publish some detailed numbers to confirm its performance and efficiency!

I am the founder of RisingWave (http://risingwave.com/), an open-source SQL streaming database. I am happy to see the launch of Warpstream! I just reviewed the project and here's my personal opinion:

* Apache Kafka is undoubtedly the leading product in the streaming platform space. It offers a simple yet effective API that has become the golden standard. All streaming/messaging vendors need to adhere to Kafka protocol.

* The original Kafka only used local storage to store data, which can be extremely expensive if the data volume is large. That's why many people are advocating for the development of Kafka Tiered Storage (KIP-405: https://cwiki.apache.org/confluence/display/KAFKA/KIP-405%3A...). To my best knowledge, there are at least five vendors selling Kafka or Kafka-compatible products with tiered storage support:

-- Confluent, which builds Kora, the 10X Kafka engine: https://www.confluent.io/10x-apache-kafka/;

-- Aiven, the open-source tiered storage Kafka (source code: https://github.com/Aiven-Open/tiered-storage-for-apache-kafk...

-- Redpanda Data, which cuts your TCO by 6X (https://redpanda.com/platform-tco);

-- DataStax, which commercializes Apache Pulsar (https://pulsar.apache.org/);

-- StreamNative, which commercializes Apache Pulsar (https://pulsar.apache.org/).

* WarpStream claims to be "built directly on top of S3," which I believe is a very aggressive approach that has the potential to drastically reduce costs, even compared to tiered storage. The potential tradeoff is system performance, especially in terms of latency. As new technology, WarpStream brings novelty, and definitely it also needs to convince users that the service is robust and reliable.

* BYOC (Bring Your Own Cloud) is becoming the default option. Most of the vendors listed above offer BYOC, where data is stored in customers' cloud accounts, addressing concerns about data privacy and security.

I believe WarpStream is new technology to this market, and and would encourage the team to publish some detailed numbers to confirm its performance and efficiency!