This is a continuation of the earlier posts starting with this one: http://ravinote.blogspot.com/2020/09/best-practice-from-networking.html
Web accessible Storage is touted as best for static content. Data that changes often is then said to be preferred in NoSQL or other unstructured storage. With object versioning, API and SDK, this is no longer the case. Also, when services are stateless, the data pertaining to a request can be saved in an object storage which gives. it request level granularity and http based access. This request scoping of storage makes it easy to retrieve with isolation.
Data Transfers have never been considered a virtual storage since they belong to the source. Data in transit can live in queues, cache and object storage which is good for vectorized execution.
The nature of the query language determines the kind of resolving that the data virtualization needs to do. In addition, the type of storage that the virtualization layer spans also depend on the query language.
In order to explain the difference between data virtualization over structured and unstructured storage types, we look at metadata in structure storage. All data types used are registered. Whether they are system built-in types or user defined types, the catalog helps with the resolution.
A query describing the selection of entries with the help of predicates does not necessarily have to be bound to structured or unstructured query languages. Yet the convenience and universal appeal of one language may dominate another. Therefore, in such cases whether the query language is agnostic or predominantly biased, it can be modified or rewritten to suit the needs of the software stacks. Networking products do not have to reinvent querying.
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