purpose of a replica tablet is for serving OLTP read traffic, whereas rdonly tablets are for serving analytics, or performing cluster maintenance operations like backups, or resharding. rdonly replicas are allowed exponentially. • Analytics: The retention period for messages is dictated by the application. One could potentially choose to never delete any messages and use the data for performing analytics. • Transactional: case, Vitess will create a rolled up version of the source table which can be used for realtime analytics. • Backfilling lookup vindexes: VReplication can be used to backfill a newly created lookup vindex

exponentially. • Analytics: The retention period for messages is dictated by the application. One could potentially choose to never delete any messages and use the data for performing analytics. • Transactional: case, Vitess will create a rolled up version of the source table which can be used for realtime analytics. • Backfilling lookup vindexes: VReplication can be used to backfill a newly created lookup vindex clauses will allow you to materialize real-time rollups of the source table, which can be used for analytics. The target table can have a different name from the source. For a sharded system like Vitess,

exponentially. • Analytics: The retention period for messages is dictated by the application. One could potentially choose to never delete any messages and use the data for performing analytics. • Transactional: case, Vitess will create a rolled up version of the source table which can be used for realtime analytics. • Backfilling lookup vindexes: VReplication can be used to backfill a newly created lookup vindex clauses will allow you to materialize real-time rollups of the source table, which can be used for analytics. The target table can have a different name from the source. For a sharded system like Vitess,

exponentially. • Analytics: The retention period for messages is dictated by the application. One could potentially choose to never delete any messages and use the data for performing analytics. • Transactional: case, Vitess will create a rolled up version of the source table which can be used for realtime analytics. • Backfilling lookup vindexes: VReplication can be used to backfill a newly created lookup vindex clauses will allow you to materialize real-time rollups of the source table, which can be used for analytics. The target table can have a different name from the source. For a sharded system like Vitess,

exponentially. • Analytics: The retention period for messages is dictated by the application. One could potentially choose to never delete any messages and use the data for performing analytics. • Transactional: case, Vitess will create a rolled up version of the source table which can be used for realtime analytics. • Backfilling lookup vindexes: VReplication can be used to backfill a newly created lookup vindex clauses will allow you to materialize real-time rollups of the source table, which can be used for analytics. The target table can have a different name from the source. For a sharded system like Vitess,

exponentially. • Analytics: The retention period for messages is dictated by the application. One could potentially choose to never delete any messages and use the data for performing analytics. • Transactional: case, Vitess will create a rolled up version of the source table which can be used for realtime analytics. • Backfilling lookup vindexes: VReplication can be used to backfill a newly created lookup vindex clauses will allow you to materialize real-time rollups of the source table, which can be used for analytics. The target table can have a different name from the source. For a sharded system like Vitess,

exponentially. • Analytics: The retention period for messages is dictated by the application. One could potentially choose to never delete any messages and use the data for performing analytics. • Transactional: case, Vitess will create a rolled up version of the source table which can be used for realtime analytics. • Backfilling lookup vindexes: VReplication can be used to backfill a newly created lookup vindex clauses will allow you to materialize real-time rollups of the source table, which can be used for analytics. The target table can have a different name from the source. For a sharded system like Vitess,

exponentially. • Analytics: The retention period for messages is dictated by the application. One could potentially choose to never delete any messages and use the data for performing analytics. • Transactional: case, Vitess will create a rolled up version of the source table which can be used for realtime analytics. • Backfilling lookup vindexes: VReplication can be used to backfill a newly created lookup vindex clauses will allow you to materialize real-time rollups of the source table, which can be used for analytics. The target table can have a different name from the source. For a sharded system like Vitess,