Database Design – Designing a Fitness/Weight Lifting Routine Database

WPF strongly encourages using the Command pattern, which encapsulates the logic for a given button press or menu item into an ICommand object, rather than as a code-behind event handler. The interesting part of these objects is that, in addition to the standard Execute method, also has a standard CanExecute method, which determines whether the button is enabled or not. This method can be used both by validation logic and by the permissions layer to determine whether the UI element is active.

This allows the permission logic to be "server-side", as part of the business logic, and have the UI element's visibility, "enabled-ness" and functionality linked to it using data binding, rather than manually going over the UI elements and enabling/disabling them.

This fits in with WPF's general philosphy of using the MVVM pattern, using data-bindings between the UI and the back-end view models to hide all that ugly "check the permission level and set the button's property accordingly" boilerplate logic.

While I agree with your premise that NoSQL is not a panacea for all database woes, I think you misunderstand one key point.

In NoSQL database you have only one criterion you can search for effectively - the key.

This is clearly not true.

For example MongoDB supports indices. (from https://docs.mongodb.org/v3.0/core/indexes-introduction/)

Indexes support the efficient execution of queries in MongoDB. Without indexes, MongoDB must perform a collection scan, i.e. scan every document in a collection, to select those documents that match the query statement. If an appropriate index exists for a query, MongoDB can use the index to limit the number of documents it must inspect.

Indexes are special data structures [1] that store a small portion of the collection’s data set in an easy to traverse form. The index stores the value of a specific field or set of fields, ordered by the value of the field. The ordering of the index entries supports efficient equality matches and range-based query operations. In addition, MongoDB can return sorted results by using the ordering in the index.

As does couchbase (from http://docs.couchbase.com/admin/admin/Views/views-intro.html)

Couchbase views enable indexing and querying of data.

A view creates an index on the data according to the defined format and structure. The view consists of specific fields and information extracted from the objects in Couchbase.

In fact anything that calls itself a NoSQL database rather than a key-value store should realy support some kind of indexing schemes.

In fact, it is often the flexibility of these index schemes that makes NoSQL shine. In my opinion, the language used to define the NoSQL indices are often more expressive or natural than SQL, and since they usually live outside the table, you don't need to change your table schemas to support them. (Not to say you cant do similar things in SQL but to me it feels like there is a lot more hoop-jumping involved).