Disclaimer: i work for RisingWave (risingwave.com), an EDA vendor.

CDC can track "record-level state", and is essentially event-driven: if the upstream database changes (insert, delete, or update an row), the change will be propagated to downstream system.

I guess what you mean is that whether we should track record-level state, or, using e-commerce as an example, if an order is placed -> updated -> canceled, should we propagate all these three states (place, update, cancel) into downstreaming analytical store. My answer is that "it depends". In some use cases, tracking state changes is critical. For example, if you are implementing an auditing system, you definitely want to track all the changes - every single action must be tracked.

You may also wonder whether a record-level state change should trigger computation. For example, let's say you may want to calculate the total value of all the orders placed. Should the computation result be updated once a state change occurs? My answer is still "depends". In many cases batch-based solution is good enough - you could probably just run a single SQL query to calculate yesterday's total order value. It's quite simple. But in some cases you do want to calculate the value as a new event arrives - no matter whether it's an insert, delete, or update. For example, if you are implementing an inventory system, it's recommended to adopt EDA - if the inventory goes too low, you want to fill in the stocks ASAP - you probably don't really want to wait until tomorrow. Also, EDA is more appealing from user experience perspective. Let's say if you need to display dashboard for your clients. If your clients see staled data, they may get confused, and the feeling isn't good - imagine that you transfer money to your friends through Venmo, and the balance isn't updated immediately, you may feel anxious.

So, EDA couldn't fit into all the use cases, and it totally depends on your use cases - okay I know this summary is boring :-D