关于SnappyData是否支持Read-Through缓存机制的技术问询

Great question! Yes, SnappyData fully supports the Read-Through caching pattern you described, and it’s built specifically to simplify your application’s data interactions by abstracting the underlying data store.

Here’s how it works in practice:

• When your application sends an SQL query to SnappyData, the system first checks its in-memory cache (and any configured disk-based storage layers) for the requested data.
• If the data is already present in the cache, it’s returned to your application immediately—no round-trip to the backend store is needed.
• If the data isn’t found in the cache (a cache miss), SnappyData will automatically fetch the required data from your configured SQL-compatible backend storage, load that data into its cache, and then send the result back to your application.

To enable this behavior, you’ll typically define cached tables or external tables in SnappyData that are directly linked to your backend data store. This tells SnappyData exactly where to pull missing data from when a Read-Through operation is triggered. The biggest benefit? Your application never has to handle direct connections to the underlying storage—it only needs to interact with SnappyData’s SQL interface.

内容的提问来源于stack exchange，提问作者Frans