Previously, AppSync addressed offline use cases by utilizing an on-device cache to store query results that have been previously returned from the cloud. AppSync’s implementation of on-device caching of query results enabled developers to create a broad range of offline capable apps. However, the data available to the app when a device was offline was limited to the contents of the cache. Therefore, developers were required to anticipate potential offline data requirements by issuing broader queries when the device was online. Now, by using Amplify DataStore, developers can build highly interactive, collaborative apps that support a wider range of offline use cases, providing more flexible access to local data. These use cases range from field service apps that allow searching, creating, and manipulating service requests when offline and real-time updates to chatrooms, whiteboards, and dashboards, to high performance use cases, such as those that require facial recognition algorithms that avoid network latencies by synchronizing ML models locally and optimized network utilization use cases such as those required by smart electricity meters that send per minute average data instead of collected data, with a local-first and familiar programming model that is easy for developers to reason about.