Sql-server – Advantage of exposing data model to customers using our product

First of all, what type of security model do you plan to implement? Role-based Access Control (RBAC) or Discretionary Access Control (DAC)?

RBAC in the Role-Based Access Control (RBAC) model, access to resources is based on the role assigned to a user. In this model, an administrator assigns a user to a role that has certain predetermined right and privileges. Because of the user's association with the role, the user can access certain resources and perform specific tasks. RBAC is also known as Non-Discretionary Access Control. The roles assigned to users are centrally administered.

DAC In the Discretionary Access Control (DAC) model, access to resources is based on user's identity. A user is granted permissions to a resource by being placed on an access control list (ACL) associated with resource. An entry on a resource's ACL is known as an Access Control Entry (ACE). When a user (or group) is the owner of an object in the DAC model, the user can grant permission to other users and groups. The DAC model is based on resource ownership.

see source

1) In RBAC: you need ElementType table to assign rights to role (users are assigned to role(s)). RBAC defines: "What can this role/user do". Administrator assigns rights for roles and permissions to roles, assigns users to role(s) to access resources. 2) In DAC: users and roles have rights to elements via access control list (ownership). DAC defines: "who has access to my data". User (owner) grants permissions to owned resource.

Any way I suggest this data model:

CREATE TABLE ElementType
(
    Id (PK)
    Name
    ...
)

CREATE TABLE ElementBase
(
    Id (PK)
    Type (FK to ElementType)
    ...
)

(one to one relationship)

CREATE TABLE Element_A
(
    Id (PK, FK to ElementBase)
    ...
)

CREATE TABLE Element_B
(
    Id (PK, FK to ElementBase)
    ...
)

1) RBAC (many-to many relationship)

CREATE TABLE ElementType_To_Role_Rights
(
    RightId (PK)
    RoleId  (FK to Role)
    ElementTypeId (FK to ElementType)
    ...
)

2) DAC (many-to many relationship)

CREATE TABLE ElementBase_To_Actor_Rights
(
    RightId (PK)
    ElementBaseId (FK to ElementBase)
    ActorId (FK to Actor)
    ...
)

CREATE TABLE Actor
(
    Id (PK)
    Name
)

CREATE TABLE User
(
    Id (PK, FK to Actor)
    Password
    ...
)

CREATE TABLE Role
(
    Id (PK, FK to Actor)
    ...
)

I think the best way to approach this would be to have tables like so:

table Customer
    ID
    Name
    ...

table CustomerFields
    CustomerID
    FieldID
    FieldName
    ... (could have things like type, required/optional, size, etc.)

table CustomerOrders
    CustomerID
    OrderID
    OrderNumber
    DeliveryDate
    ... (all your generics and mappable fields)

table CustomerOrderFields
    CustomerID
    OrderID
    FieldID
    FieldValue

By having the table CustomerOrders, you satisfy the ability to map common customer order data to common fields (simplifying reporting at the expense of making the import a little more painful since the fields must be mapped), and the CustomerOrderFields gives you the ability to have the custom fields per customer necessary for the un-mappable data.

The custom fields are still reportable, but not as easily as your generics as they'll come to you in multiple rows (instead of multiple columns). There are some ways around all that depending on your report creator (e.g., pivoting the results).

The only other option would be to do something like this (which, personally, I would avoid):

table CustomerFields
    CustomerID
    Field1Name
    Field2Name
    Field3Name
    ...
    Field99Name

Table CustomerOrders
    (all your generics)
    Field1Value
    Field2Value
    ...
    Field99Value

This has the advantage that all your data is in one row, but also has the disadvantage that it isn't immediately apparent from the row what each value means. The first method can always be joined to the field list to give a good definition of the data in each custom field. In addition, what happens if some company requires 100 custom fields? In the above example, you'd be making changes to your data structures and code whereas in the first example, you'd never have the issue -- customers could have infinite custom fields.

I've seen it done both ways, and both ways work. Both ways have their downsides and upsides. The first is far more scalable, but harder to get in to columns (instead of rows). Everything's a trade-off.

Hope that helps some!