Technologies are generally provided for conveying tree and index needs of a database by collecting and forwarding a statistically representative set of data requests so that a new datacenter can use its existing auto-learning and adjustment techniques to create local indices before receiving its first real or live requests. In some examples, requests at an origin datacenter may be collected to provide a small population of queries that are representative of a larger population of queries. Filters anonymizers may be employed to adhere to data sharing rules and restrictions while still allowing a new datacenter to build indices and test performance. Thus, the new datacenter may be trained asynchronously from another site and without actual data changing hands. Training and testing of destination database services may be completed before committing to customer migration.