------------------------------------- Performing queries across billions of metrics looking for labels that only match a few of them (a common scenario with time series data at scale) is really slow in Cassandra. This is because of the way it stores data in columns. This extends to any columnar database including Google's BigQuery which all have a natural disadvantage with time series data. -------------------------------------
There's nothing inherently limiting in columnar databases that makes it slow to match only a few elements that match only a few out of billions or trillions of records.
... but a classic columnar store might not be as efficient for storage, or might take 5-10x the nodes to return with the same speed with that kind of filtering, depending on storage and clustering mechanisms used.