Rudderstack VS Apache Kafka

If CDP(such as RudderStack) were a restaurant, then Data Integration is the guy that gets all raw ingrediants from different shops and makes it available to Chef that sorts and combines raw ingrediants to make a dish. The chef can't cook anything without raw ingrediamt. Similarly Data Integration is also an important component in CDP that collects customer data from various sources and them other components unify it and activate it.

More details on GitHub repository - https://github.com/rudderlabs/rudder-server

Are you RudderStack?

In bigger setups, all you want is a data collector and router so that you can feed the data into multiple destinations, depending on the use case. Analytics is just one. Example: https://www.rudderstack.com/ & https://www.rudderstack.com/replace-google-analytics-4-guide...

Check out RudderStack, a Go project to build data pipeline. Our slack is quite active. The best way to contribute is by creating a new integration with your favorite tool. You do not need to rely to too much on existing knowledge about inner workings of the project to do so, so it is beginner friendly.

Interesting. About "Redshift need google sheet sync to table", wouldn't this be more aligned with the responsibility of a CDP(such as RudderStack) as opposed to something we expext a warehouse to do?

The challenge is over. Winners have been announced. When we are ready for the next one, will announce on RudderStack GitHub repo

Super. This is amazing. Sharing your project with the community. If you get a chance, try out RudderStack to build your pipeline.

Apache Kafka — a distributed event streaming platform implementing a variant of the Raft consensus protocol (written in Java, integrated with Scala);

Spring does this during autoconfiguration. For example this and this. When the user adds a configuration then it gets to overwrite the default from the template. I am looking for something similar, perhaps simpler approach.

Source and documentation on GitHub

Code is still in trunk though. https://github.com/apache/kafka/tree/trunk/connect/file/src/main/java/org/apache/kafka/connect/file

I briefly described the algorithm in this article and there is a wonderful article from Kafka that goes into more depth in their general purpose implementation. My implementation is specialized and over optimized in comparison, e.g. by using bit manipulation to avoid more expensive division/modulus instructions. Tokio rewrote their timerwheel after I showed them mine, borrowing some ideas but also staying more general. Hope that helps!

Apache Kafka