How can you synchronize data between a mobile app and a web server?

1-Develop a RESTful API or GraphQL endpoint on the web server that the mobile app can interact with 2-Decide best data transfer formats, such as JSON or XML. 3-Implement offline data handling mechanisms in the mobile app. 4-Define a synchronization strategy to handle conflicts when the same data is modified simultaneously. Strategies may include timestamp-based conflict resolution, optimistic concurrency control, or manual conflict resolution by the user. 5-Implement delta synchronization to reduce the amount of data transferred. 6-Implement error handling and retry mechanisms in both the mobile app and the server. 7-Set up monitoring and logging to track synchronization, identify performance bottlenecks.

Taking question literally here: The first step in data synchronization is for devices and servers to agree what is the current time is. Data format is completely irrelevant

In data synchronization, the initial phase entails defining the data models and formats utilized by both the mobile app and web server. Data models represent the logical structures embodying entities and relationships within the domain, while data formats denote the physical representations of the data, including JSON, XML, or binary. It is imperative to select data models and formats that align seamlessly across the application and server, ensuring compatibility and consistency. Moreover, prioritizing ease of parsing, validation, and manipulation is crucial.

In data synchronization, the initial phase entails defining the data models and formats utilized by both the mobile app and web server. Data models represent the logical structures embodying entities and relationships within the domain, while data formats denote the physical representations of the data, including JSON, XML, or binary. It is imperative to select data models and formats that align seamlessly across the application and server, ensuring compatibility and consistency. Moreover, prioritizing ease of parsing, validation, and manipulation is crucial.

The 2 drivers here are your User Interface (what the client sees) and the Database Tables/Entities (what's possible). Most of the time the UI will only need to display a small portion of the data fields that are available. Define data models that provide only that data that is required for the current purpose. I typically define a Data Transfer Object (DTO) which only contains the required properties. This keeps your payloads small and efficient and doesn't expose any data you might not want to share. Take advantage of automation where possible. Use MapStruct to copy the entity properties to the DTO and Jackson to convert the DTO to JSON for transport over HTTP to the client. Reverse the process on the client for error free data transfers.

There is little alternative to using Internet Protocol over some sort of radio communication for mobile-to-server interaction. So - no decision is really necessary. Storage and retrieval (read/write) have to be done over the Internet wireless connections.

The type of data storage and retrieval should be driven by the types of data you are managing and the platforms you are running on, as well as the application framework in use. Most non-trivial applications will benefit by using a relational database. Use a NoSQL database to quickly look up key-value pairs. Pick a mix that minimizes the amount of coding required. For example, using Panache for Entity management in Quarkus based applications eliminates a lot of SQL and code to copy data from result sets to objects. But don't shy away from SQL where it makes sense. It's not difficult and it's extremely powerful.

Prioritize in this order: Pushing, Syncing and finally Polling. Always adjust the synchronization method to fit the use case and minimizes chattiness. When starting a mobile app, request all data modified since the last login by comparing the record's date-modified field against the user's last login timestamp. Cache data locally, especially if it doesn't change frequently to reduce unnecessarily transferring data.

The question is ambiguous: is it about synchronization (timing) of the data or consistency (possibly eventual consistency)? In either case it is super important to have solid requirements (based on the actual user-facing problem being solved). Then, independent of the data format (it can be all abstracted as binary) there is a mix of the following approaches: For time consistency (as in multiplayer online games): - lag estimation (probably separate up/down stream), prediction and compensation. - Timestamp synchronization between devices (for example using NTP based on server time). - Device clock skew estimation and prediction. For data consistency (as in transactions): - decide where “data objects” reside. - implement atomicity - …