In general I'd expect native partitioning to have similar performance characteristics as TimescaleDB. On the insert side lot of the benefit comes from partitions having small indexes, on the delete side from the ability to drop partitions quickly, and on the select side from skipping partitions based on filters.

Postgres 10 partitioning does have a few limitations and inefficiencies that will be resolved in Postgres 11. Partitioning is the most actively developed area of postgres.

Note that Citus shards across multiple nodes, and can then partition on disk using native partitioning, which is automated by pg_partman. TimescaleDB so far only works on a single node.

Citus can also run parallel, distributed SQL queries, perform distributed transactions, and build rollups tables in parallel, and is used in Postgres clusters with up to a petabyte of data.

From everything I've seen on it, Citus makes horizontally scaling a multi-tenant database a transparent operation. This is ideal just because so many applications emphasize recency in the data that you don't want rarely accessed, 3 year old information cluttering up your indexes that are looking up things from this month 99% of the time.

Timescale seems to me more about the analytics side of things, focusing on ingestion speed and aggregation. Correct me if I'm wrong somebody.