Dynamic distributed data clustering

Techniques are described for clustering data at the point of ingestion for storage using scalable storage resources. The clustering techniques described herein are used to cluster time series data in a manner such that data that is likely to be queried together is localized to a same partition, or to a minimal set of partitions if the data set is large, where the partitions are mapped to physical storage resources where the data is to be stored for subsequent processing. Among other benefits, the clustered storage of the data at the physical storage resources can reduce an amount of data that needs to be filtered by many types of queries, thereby improving the performance of any applications or processes that rely on querying the data.