I think that it would be better for you to position CitusDB by comparing it to other products in terms of use cases.
If the data is big and I need to run analytic queries then I think I have to use a columnar storage format because row-oriented formats cause too much overhead for aggregation queries that usually need to process single column efficiently. If I use CitusDB as an analytical database, then it's comparable with Redshift, Hive etc. As you said, they're suitable for offline data but Can I use cstore_fdw in CitusDB and able to take advantage of real-time nature of Postgresql? Maybe I can push hot data to a table that use row-oriented format and move the data periodically to another table that uses cstore_fdw and execute queries that fetches data from both cold storage and hot storage tables? If CitusDB makes it easy for me, then I think this is huge.
I guess another use case is using CitusDB as distributed data store and executing filter queries such as "SELECT * FROM table WHERE partition_key = x and predicate1 = y ...". Instead of using multiple Postgresql instances and routing the queries in application level, I can just use CitusDB that takes care of replication && query routing && sharding etc. I think it can also be comparable to databases such as Cassandra, Mongo (using jsonb) since they also have similar use-cases.
Or should I think CitusDB as distributed Postgresql?