We have a situation in a database design in our company. We are trying to figure out the best way to design the database to store transactional data. I need expert’s advice on the best relational design to achieve it. Problem: We have different kind of “Entities” in our system, for example; Customers, Services, Dealers etc. These Entities are doing transfer of funds between each other. We need to store the history of the transfers in database.
Solutions:
One table of transfers and another table to keep “Accounts” information. There are three tables “Customers”, “Services”, “Dealers”. There is another table “Accounts”. An account can be related to any of the “Entities” mentioned above; it means (and that’s the requirement) that logically there should be a one-to-one relationship to/from Entities and Accounts. However, we can only store the Account_ID in the Entities table, but we cannot store the foreign key of Entities in Accounts table. Here the problem happens in terms of database design. Because if there is a customer’s account, it is not restricted by the database design to not be stored in Services table etc. Now we can keep all transfers in one table only since Accounts are unified among all the entities.
Keep the balance information in the table primary Entities table and separate tables for all transfers. Here for all kind of transfers between the entities, we are keeping separate tables. For example, a transfer between a Customer and Service provider will be stored in a table called “Spending”. Another table will have transfer data for transfer between Service and Dealers called “Commission” etc. In this case, we are not storing all the transfers of the funds in a single table, but the foreign keys are properly defined since the tables “Spending” and “Commission” are only between two specific entities.
According to the best practices, which one of the above given solutions is correct, and why?
If you are simply looking for schemas that claim to deal with cases like yours, there is a website with hundreds of published schemas. Some of these pertain to storing transaction data concerning customers and suppliers. You can take one of these and adapt it.
http://www.databaseanswers.org/data_models/
If your question is about how to relate accounts to business contacts, read on.
Customers, Services, and Dealers are all sub classes of some super class that I'll call Contacts. There are two well known design patterns for modeling sub classes in database tables. And there is a technique called Shared primary Key that can be used with one of them to good advantage.
Take a look at the info and the questions grouped under these three tags:
single-table-inheritance class-table-inheritance shared-primary-key
If you use class table inheritance and shared primary key, you will end up with four tables pertaining to contacts: Contacts, Customers, Dealers, and Services. Every entry in Contacts will have a corresponding entry in one of the three subclass tables.
An FK in the accounts table, let's call it Accounts.ContactID will not only reference a row in Contacts, but also a row in whichever of Customers, Dealers, Services pertains to the case at hand.
This may work outwell for you. Alternatively, single table table inheritance works out well in some of the simpler cases. It depends on details about your data and your intended use of it.
You can make table Accounts with three fields with FK to Customers,Dealers and Services and it's will close problem. But also you can make three table for each type of entity with accounting data. You have the deal with multi-system case in system design. Each system solve the task. But for deсision you need make pros and con analyses about algorithm complexity, performance and other system requirements. For example one table will be more simple to code, but three table give more performance of sql database.
Related
Recently I encountered an application, Where a Master Table is maintained which contain the data of more than 20 categories. For e.g. it has some categories named as Country,State and City.
So my question is, it is better to move out this category as a separate table and fetching out the data through joins or Everything should be inside a single table.
P.S. In future categories count might increase to 50+ or more than it.
P.S. application based on EF6 + Sql Server.
Edited Version
I just want to know that in above scenario what should be the best approach, one should go with single table with proper indexing or go by the DB normalization approach, putting each category into a separate Table and maintaning relationship through fk's.
Normally, categories are put into separate tables. This conforms more closely with normalized database structures and the definition of entities. In particular, it allows for proper foreign key relationships to be defined. That is a big win for data integrity.
Sometimes categories are put into a single table. This can, of course, be confusing; consider, for instance, "Florida, Massachusetts" or "Washington, Iowa" (these are real places).
Putting categories in one table has one major advantage: all the text is in a single location. That can be very handy for internationalization efforts. To be honest, that is the situation where I have seen this used.
In database design what are the feelings of tuple vs referencing table for small pieces of data?
For instance, supposing you are designing a schema involving office management. You want to record what department each employee belongs to, but are otherwise uninterested in any information relating to departments. So do you have department as a string/char/varchar/etc in your EMPLOYEE table, or have it instead be a foreign key, relating a DEPARTMENT table.
If the DEPARTMENT table is recording nothing other than department names, one would normally want to combine this with the EMPLOYEE table. But if this is contained in the EMPLOYEE table you cannot guarantee that some users will call HR "HumanResourses", some may call it "H-R", some may call it "human resources", etc. Having it as a foreign key guarantees that it can be only one thing. Also, if other information is ever to be added about departments, it would be easy if it is in a table of its own.
So what do people think about it? Naturally more tables and referencing is also likely to have a negative impact on performance. My question specifically is asked with Oracle 11g in mind, but I doubt that the type of rdms involved has much bearing on this design consideration.
If you use the related table, then you don't have the performance problem of updating 1,000,000 records because the Personnel Department became the Human Resources department.
You have another option. Create the table and use it as a lookup for data entry. But store the information in the main table.
However, I prefer the option of using the related table for the departments and storing the ID for the department and the employee in a join table that has the ids and start and endates. Over time employees tend to move from one department to another. It is helpful for reporting to be able to tell what department they were in when. You need to consider how the data will be used over time and in reporting when designing this sort of thing. Short-sighted designs are hard to fix later.
Your concern about having too many tables is really unfounded. Databases are designed to have many tables and to use joins. If you index correctly, there will not be preformance implications for most databases. And you know what,I know of realtional database with many many tables that have terrabytes of data that perform just fine.
You only have to worry about the performance impact of this sort of thing if you're dealing with truly massive datasets. For any regular office environment system like this, prefer the normalized schema.
This question may answer itself, but it is also a question of best practices.
I am designing an application that allows users (comapnies) to create an account. Those users are placed in a table "Shop_table". Now each shop has dynamic data, however the tables would be the same for each shop, like shop_employees, shop_info, shop_data.
Would it be more effective to have a specific table for each shop or would I just link their data by the shop id.
For example:
shop: Dunkins with id:1
shop: Starbucks with id:2
would dunkins have its own dunkins_shop_employees, dunkins_shop_info, dunkins_shop_data tables
and Starbucks have its own starbucks_shop_employees , starbucks_shop_info , starbucks_shop_data
or would i have one table shope_employees, shop_info, shop_data and link by id 1 or 2, etc..
Definitely one table for each entity with a field to identify the company.
If all the companies have the same information there is no need to create tables for each, and if you did your queries will become a nightmare.
Do you really want a load of UNION queries in order to get any aggregate data across companies? You will also have to modify all queries in your DB as soon as another company (and therefore multiple tables) are added.
Define your tables independently, model the entities you want to store and dont think about who they belong to.
You should have only one table ( for each shop_info etc.. )
Creating similar tables is a maintenance nightmare. You will need to create similar foreign keys, similar constraints, similar indexes, etc.
If your concern is privacy, this should be controlled in your application. You application should always add a "WHERE" clause based on who is logged in/ querying.
If you absolutely need to - you can create views which where clause as shop_id. You can give rights to various people on the view only. This would only make sense if you had a big customer who wanted some SQL level query ability.
Consider we have a database that has a table, which is a record of a sale. You sell both products and services, so you also have a product and service table.
Each sale can either be a product or a service, which leaves the options for designing the database to be something like the following:
Add columns for each type, ie. add Service_id and Product_id to Invoice_Row, both columns of which are nullable. If they're both null, it's an ad-hoc charge not relating to anything, but if one of them is satisfied then it is a row relating to that type.
Add a weird string/id based system, for instance: Type_table, Type_id. This would be a string/varchar and integer respectively, the former would contain for example 'Service', and the latter the id within the Service table. This is obviously loose coupling and horrible, but is a way of solving it so long as you're only accessing the DB from code, as such.
Abstract out the concept of "something that is chargeable" for with new tables, of which Product and Service now are an abstraction of, and on the Invoice_Row table you would link to something like ChargeableEntity_id. However, the ChargeableEntity table here would essentially be redundant as it too would need some way to link to an abstract "backend" table, which brings us all the way back around to the same problem.
Which way would you choose, or what are the other alternatives to solving this problem?
What you are essentially asking is how to achieve polymorphism in a relational database. There are many approaches (as you yourself demonstrate) to this problem. One solution is to use "table per class" inheritance. In this setup, there will be a parent table (akin to your "chargeable item") that contains a unique identifier and the fields that are common to both products and services. There will be two child tables, products and goods: Each will contain the unique identifier for that entity and the fields specific to it.
One benefit to this approach over others is you don't end up with one table with many nullable columns that essentially becomes a dumping ground to describe anything ("schema-less").
One downside is as your inheritance hierarchy grows, the number of joins needed to grab all the data for an entity also grows.
I believe it depends on use case(s).
You could put the common columns in one table and put product and service specific columns in its own tables.Here the deal is that you need to join stuff.
Else if you maintain two separate tables, one for Product and another for Sale. You use application logic to determine which table to insert into. And getting all sales will essentially mean , union of getting all products and getting all sale.
I would go for approach 2 personally to avoid joins and inserting into two tables whenever a sale is made.
I am having a hard time trying to figure out when to use a 1-to-1 relationship in db design or if it is ever necessary.
If you can select only the columns you need in a query is there ever a point to break up a table into 1-to-1 relationships. I guess updating a large table has more impact on performance than a smaller table and I'm sure it depends on how heavily the table is used for certain operations (read/ writes)
So when designing a database schema how do you factor in 1-to-1 relationships? What criteria do you use to determine if you need one, and what are the benefits over not using one?
From the logical standpoint, a 1:1 relationship should always be merged into a single table.
On the other hand, there may be physical considerations for such "vertical partitioning" or "row splitting", especially if you know you'll access some columns more frequently or in different pattern than the others, for example:
You might want to cluster or partition the two "endpoint" tables of a 1:1 relationship differently.
If your DBMS allows it, you might want to put them on different physical disks (e.g. more performance-critical on an SSD and the other on a cheap HDD).
You have measured the effect on caching and you want to make sure the "hot" columns are kept in cache, without "cold" columns "polluting" it.
You need a concurrency behavior (such as locking) that is "narrower" than the whole row. This is highly DBMS-specific.
You need different security on different columns, but your DBMS does not support column-level permissions.
Triggers are typically table-specific. While you can theoretically have just one table and have the trigger ignore the "wrong half" of the row, some databases may impose additional limits on what a trigger can and cannot do. For example, Oracle doesn't let you modify the so called "mutating" table from a row-level trigger - by having separate tables, only one of them may be mutating so you can still modify the other from your trigger (but there are other ways to work-around that).
Databases are very good at manipulating the data, so I wouldn't split the table just for the update performance, unless you have performed the actual benchmarks on representative amounts of data and concluded the performance difference is actually there and significant enough (e.g. to offset the increased need for JOINing).
On the other hand, if you are talking about "1:0 or 1" (and not a true 1:1), this is a different question entirely, deserving a different answer...
See also: When I should use one to one relationship?
Separation of duties and abstraction of database tables.
If I have a user and I design the system for each user to have an address, but then I change the system, all I have to do is add a new record to the Address table instead of adding a brand new table and migrating the data.
EDIT
Currently right now if you wanted to have a person record and each person had exactly one address record, then you could have a 1-to-1 relationship between a Person table and an Address table or you could just have a Person table that also had the columns for the address.
In the future maybe you made the decision to allow a person to have multiple addresses. You would not have to change your database structure in the 1-to-1 relationship scenario, you only have to change how you handle the data coming back to you. However, in the single table structure you would have to create a new table and migrate the address data to the new table in order to create a best practice 1-to-many relationship database structure.
Well, on paper, normalized form looks to be the best. In real world usually it is a trade-off. Most large systems that I know do trade-offs and not trying to be fully normalized.
I'll try to give an example. If you are in a banking application, with 10 millions passbook account, and the usual transactions will be just a query of the latest balance of certain account. You have table A that stores just those information (account number, account balance, and account holder name).
Your account also have another 40 attributes, such as the customer address, tax number, id for mapping to other systems which is in table B.
A and B have one to one mapping.
In order to be able to retrieve the account balance fast, you may want to employ different index strategy (such as hash index) for the small table that has the account balance and account holder name.
The table that contains the other 40 attributes may reside in different table space or storage, employ different type of indexing, for example because you want to sort them by name, account number, branch id, etc. Your system can tolerate slow retrieval of these 40 attributes, while you need fast retrieval of your account balance query by account number.
Having all the 43 attributes in one table seems to be natural, and probably 'naturally slow' and unacceptable for just retrieving single account balance.
It makes sense to use 1-1 relationships to model an entity in the real world. That way, when more entities are added to your "world", they only also have to relate to the data that they pertain to (and no more).
That's the key really, your data (each table) should contain only enough data to describe the real-world thing it represents and no more. There should be no redundant fields as all make sense in terms of that "thing". It means that less data is repeated across the system (with the update issues that would bring!) and that you can retrieve individual data independently (not have to split/ parse strings for example).
To work out how to do this, you should research "Database Normalisation" (or Normalization), "Normal Form" and "first, second and third normal form". This describes how to break down your data. A version with an example is always helpful. Perhaps try this tutorial.
Often people are talking about a 1:0..1 relationship and call it a 1:1. In reality, a typical RDBMS cannot support a literal 1:1 relationship in any case.
As such, I think it's only fair to address sub-classing here, even though it technically necessitates a 1:0..1 relationship, and not the literal concept of a 1:1.
A 1:0..1 is quite useful when you have fields that would be exactly the same among several entities/tables. For example, contact information fields such as address, phone number, email, etc. that might be common for both employees and clients could be broken out into an entity made purely for contact information.
A contact table would hold common information, like address and phone number(s).
So an employee table holds employee specific information such as employee number, hire date and so on. It would also have a foreign key reference to the contact table for the employee's contact info.
A client table would hold client information, such as an email address, their employer name, and perhaps some demographic data such as gender and/or marital status. The client would also have a foreign key reference to the contact table for their contact info.
In doing this, every employee would have a contact, but not every contact would have an employee. The same concept would apply to clients.
Just a few samples from past projects:
a TestRequests table can have only one matching Report. But depending on the nature of the Request, the fields in the Report may be totally different.
in a banking project, an Entities table hold various kind of entities: Funds, RealEstateProperties, Companies. Most of those Entities have similar properties, but Funds require about 120 extra fields, while they represent only 5% of the records.