Rapidly handling large data sets can be a challenge, particularly in situations where there are millions or even hundreds of millions of database records. Sometimes, however, a service level agreement necessitates that a service return a response to a query in a small amount of time. Database organization techniques can be used that reduce potentially large datasets to smaller groups (neighbors) based on uncommon but shared attributes, in various instances. Using a limited set of related records, queries can be answered using a focused approximation based on characteristics of various identified clusters of records in the set of related records. A particular record may also be associated with an existing cluster of records based on that record's similarities to records in the cluster.