Processing ingested data to identify anomalies

Systems and methods are described for processing ingested data in an asynchronous manner as the data is being ingested to detect potential anomalies. For example, one or more streaming data processors can convert data as the data is ingested into a comparable data structure, determine whether the comparable data structure should be assigned to an existing data pattern or a new data pattern, and optionally update a characteristic of the data pattern to which the comparable data structure is assigned. The streaming data processor(s) can perform these operations automatically in real-time or in periodic batches. Once one or more comparable data structures have been assigned to one or more data patterns, the streaming data processor(s) can analyze the comparable data structures assigned to a particular data pattern to determine whether any of the comparable data structures appear to be anomalous.