I'm preparing a legacy Microsoft SQL Server database so that I can interface with in through an ORM such as Entity Framework, and my question revolves around handling the setup of some of my many-to-many associations that share a common type. Specifically, should a common type be shared among master types or should each master type have its own linked table?
For example, here is a simple example I concocted that shows how the tables of interest are currently setup:
Notice that of there are two types, Teachers and Students, and both can contain zero, one, or many PhoneNumbers. The two tables, Teachers and Students, actually share an association table (PeoplePhoneNumbers). The field FKID is either a TeacherId or a StudentId.
The way I think it ought to be setup is like this:
This way, both the Teachers table and the Students table get its own PhoneNumbers table.
My gut tells me the second way is the proper way. Is this true? What about even if the PhoneNumbers tables contains several fields? My object oriented programmer brain is telling me that it would be wrong to have several identical tables, each containing a dozen or so fields if the only difference between these tables is which master table they are linked to? For example:
Here we have two tables that contain the same information, yet the only difference is that one table is addresses for Teachers and the other is for Students. These feels redundant to me and that they should really be one table -- but then I lose the ability for the database to constrain them (right?) and also make it messier for myself when I try to apply an ORM to this.
Should this type of common type be merged or should it stay separated for each master type?
Update
The answers below have directed me to the following solution, which is based on subclassing tables in the database. One of my original problems was that I had a common table shared among multiple other tables because that entity type was common to both the other tables. The proper way to handle that is to subclass the shared tables and essentially descend them from a common parent AND link the common data type to this new parent. Here's an example (keep in mind my actual database has nothing to do with Teachers and Students, so this example is highly manufactured but the concepts are valid):
Since Teachers and Students both required PhoneNumbers, the solution is to create a superclass, Party, and FK PhoneNumbers to the Party table. Also note that you can still FK tables that only have to do with Teachers or only have to do with Students. In this example I also subclassed Students and PartTimeStudents one more level down and descended them from Learners.
Where this solution is very satisfactory is when I implement it in an ORM, such as Entity Framework.
The queries are easy. I can query all Teachers AND Students with a particular phone number:
var partiesWithPhoneNumber = from p in dbContext.Parties
where p.PhoneNumbers.Where(x => x.PhoneNumber1.Contains(phoneNumber)).Any()
select p;
And it's just as easy to do a similar query but only for PhoneNumbers belonging to only Teachers:
var teachersWithPhoneNumber = from t in dbContext.Teachers
where t.Party.PhoneNumbers.Where(x => x.PhoneNumber1.Contains(phoneNumber)).Any()
select t;
Teacher and Student are both subclasses of a more general concept (a Person). If you create a Person table that contains the general data that is shared for all people in your database and then create Student and Teacher tables that link to Person and contain any additional details you will find that you have an appropriate point to link in any other tables.
If there is data that is common for all people (such as zero to many phone numbers) then you can link to the Person table. When you have data that is only appropriate for a Student you link it to the Student ID. You gain the additional advantage that Student Instructors are simply a Person with both a Student and Teacher record.
Some ORMs support the concept of subclass tables directly. LLBLGen does so in the way I describe so you can make your data access code work with higher level concepts (Teacher and Student) and the Person table will be managed on your behalf in the low level data access code.
Edit
Some commentary on the current diagram (which may not be relevant in the source domain this was translated from, so a pinch of salt is advised).
Party, Teachers and Learners looks good. Salaries looks good if you add start and end dates for the rate so you can track salary history. Also keep in mind it may make sense to use PartyID (instead of TeacherID) if you end up with multiple entites that have a Salary.
PartyPhoneNumbers looks like you might be able to hang the phone number off of that directly. This would depend on if you expect to change the phone number for multiple people (n:m) at once or if a phone number is owned by each Party independently. (I would expect the latter because you might have a student who is a (real world) child of a teacher and thus they share a phone number. I wouldn't want an update to the student's phone number to impact the teacher, so the join table seems odd here.)
Learners to PaymentHistories seems right, but the Students vs PartTimeStudents difference seems artificial. (It seems like PartTimeStudents is more AttendenceDays which in turn would be a result of a LearnerClasses join).
I think you should look into the supertype/subtype pattern. Add a Party or Person table that has one row for every teacher or student. Then, use the PartyID in the Teacher and Student tables as both the PK and FK back to Party (but name them TeacherID and StudentID). This establishes a "one-to-zero-or-one" relationship between the supertype table and each of the subtype tables.
Note that if you have identity columns in the subtype tables they will need to be removed. When creating those entities going forward you will first have to insert to the supertype and then use that row's ID in either subtype.
To maintain consistency you will also have to renumber one of your subtype tables so its IDs do not conflict with the other's. You can use SET IDENTITY_INSERT ON to create the missing supertype rows after that.
The beauty of all this is that when you have a table that must allow only one type such as Student you can FK to that table, but when you need an FK that can be either--as with your Address table--you FK to the Party table instead.
A final point is to move all the common columns into the supertype table and put only columns in the subtypes that must be different between them.
Your single Phone table now is easily linked to PartyID as well.
For a much more detailed explanation, please see this answer to a similar question.
The problem that you have is an example of a "one-of" relationship. A person is a teacher or a student (or possibly both).
I think the existing structure captures this information best.
The person has a phone number. Then, some people are teachers and some are students. The additional information about each entity is stored in either the teacher or student table. Common information, such as name, is in the phone table.
Splitting the phone numbers into two separate tables is rather confusing. After all, a phone number does not know whether it is for a student or a teacher. In addition, you don't have space for other phone numbers, such as for administrative staff. You also have a challenge for students who may sometimes teach or help teach a class.
Reading your question, it looks like you are asking for a common database schema to your situation. I've seen several in the past, some easier to work with than others.
One option is having a Student_Address table and a Teacher_Address table that both use the same Address table. This way if you have entity specific fields to store, you have that capability. But this can be slightly (although not significantly) harder to query against.
Another option is how you suggested above -- I would probably just add a primary key on the table. However you'd want to add a PersonTypeId field to that table (PersonTypeId which links to a PersonType table). This way you'd know which entity was with each record.
I would not suggest having two PhoneNumber tables. I think you'll find it much easier to maintain with all in the same table. I prefer keeping same entities together, meaning Students are a single entity, Teachers are a single entity, and PhoneNumbers are the same thing.
Good luck.
I am working on a project where there are several types of users (students and teachers). Currently to store the user's information, two tables are used. The users table stores the information that all users have in common. The teachers table stores information that only teachers have with a foreign key relating it to the users table.
users table
id
name
email
34 other fields
teachers table
id
user_id
subject
17 other fields
In the rest of the database, there are no references to teachers.id. All other tables who need to relate to a user use users.id. Since a user will only have one corresponding entry in the teachers table, should I just move the fields from the teachers table into the users table and leave them blank for users who aren't teachers?
e.g.
users
id
name
email
subject
51 other fields
Is this too many fields for one table? Will this impede performance?
I think this design is fine, assuming that most of the time you only need the user data, and that you know when you need to show the teacher-specific fields.
In addition, you get only teachers just by doing a JOIN, which might come in handy.
Tomorrow you might have another kind of user who is not a teacher, and you'll be glad of the separation.
Edited to add: yes, this is an inheritance pattern, but since he didn't say what language he was using I didn't want to muddy the waters...
In the rest of the database, there are no references to teachers.id. All other tables who need to relate to a user
use users.id.
I would expect relating to the teacher_id for classes/sections...
Since a user will only have one corresponding entry in the teachers table, should I just move the fields from the teachers table into the users table and leave them blank for users who aren't teachers?
Are you modelling a system for a high school, or post-secondary? Reason I ask is because in post-secondary, a user can be both a teacher and a student... in numerous subjects.
I would think it fine provided neither you or anyone else succumbs to the temptation to reuse 'empty' columns for other purposes.
By this I mean, there will in your new table be columns that are only populated for teachers. Someone may decide that there is another value they need to store for non-teachers, and use one of the teacher's columns to hold it, because after all it'll never be needed for this non-teacher, and that way we don't need to change the table, and pretty soon your code fills up with things testing row types to find what each column holds.
I've seen this done on several systems (for instance, when loaning a library book, if the loan is a long loan the due date holds the date the book is expected back. but if it's a short loan the due date holds the time it's expected back, and woe betide anyone who doesn't somehow know that).
It's not too many fields for one table (although without any details it does seem kind of suspicious). And worrying about performance at this stage is premature.
You're probably dealing with very few rows and a very small amount of data. You concerns should be 1) getting the job done 2) designing it correctly 3) performance, in that order.
It's really not that big of a deal (at this stage/scale).
I would not stuff all fields in one table. Student to teacher ratio is high, so for 100 teachers there may be 10000 students with NULLs in those 17 fields.
Usually, a model would look close to this:
I your case, there are no specific fields for students, so you can omit the Student table, so the model would look like this
Note that for inheritance modeling, the Teacher table has UserID, same as the User table; contrast that to your example which has an Id for the Teacher table and then a separate user_id.
it won't really hurt the performance, but the other programmers might hurt you if you won't redisign it :) (55 fielded tables ??)
I was thinking the other day on normalization, and it occurred to me, I cannot think of a time where there should be a 1:1 relationship in a database.
Name:SSN? I'd have them in the same table.
PersonID:AddressID? Again, same table.
I can come up with a zillion examples of 1:many or many:many (with appropriate intermediate tables), but never a 1:1.
Am I missing something obvious?
A 1:1 relationship typically indicates that you have partitioned a larger entity for some reason. Often it is because of performance reasons in the physical schema, but it can happen in the logic side as well if a large chunk of the data is expected to be "unknown" at the same time (in which case you have a 1:0 or 1:1, but no more).
As an example of a logical partition: you have data about an employee, but there is a larger set of data that needs to be collected, if and only if they select to have health coverage. I would keep the demographic data regarding health coverage in a different table to both give easier security partitioning and to avoid hauling that data around in queries unrelated to insurance.
An example of a physical partition would be the same data being hosted on multiple servers. I may keep the health coverage demographic data in another state (where the HR office is, for example) and the primary database may only link to it via a linked server... avoiding replicating sensitive data to other locations, yet making it available for (assuming here rare) queries that need it.
Physical partitioning can be useful whenever you have queries that need consistent subsets of a larger entity.
One reason is database efficiency. Having a 1:1 relationship allows you to split up the fields which will be affected during a row/table lock. If table A has a ton of updates and table b has a ton of reads (or has a ton of updates from another application), then table A's locking won't affect what's going on in table B.
Others bring up a good point. Security can also be a good reason depending on how applications etc. are hitting the system. I would tend to take a different approach, but it can be an easy way of restricting access to certain data. It's really easy to just deny access to a certain table in a pinch.
My blog entry about it.
Sparseness. The data relationship may be technically 1:1, but corresponding rows don't have to exist for every row. So if you have twenty million rows and there's some set of values that only exists for 0.5% of them, the space savings are vast if you push those columns out into a table that can be sparsely populated.
Most of the highly-ranked answers give very useful database tuning and optimization reasons for 1:1 relationships, but I want to focus on nothing but "in the wild" examples where 1:1 relationships naturally occur.
Please note one important characteristic of the database implementation of most of these examples: no historical information is retained about the 1:1 relationship. That is, these relationships are 1:1 at any given point in time. If the database designer wants to record changes in the relationship participants over time, then the relationships become 1:M or M:M; they lose their 1:1 nature. With that understood, here goes:
"Is-A" or supertype/subtype or inheritance/classification relationships: This category is when one entity is a specific type of another entity. For example, there could be an Employee entity with attributes that apply to all employees, and then different entities to indicate specific types of employee with attributes unique to that employee type, e.g. Doctor, Accountant, Pilot, etc. This design avoids multiple nulls since many employees would not have the specialized attributes of a specific subtype. Other examples in this category could be Product as supertype, and ManufacturingProduct and MaintenanceSupply as subtypes; Animal as supertype and Dog and Cat as subtypes; etc. Note that whenever you try to map an object-oriented inheritance hierarchy into a relational database (such as in an object-relational model), this is the kind of relationship that represents such scenarios.
"Boss" relationships, such as manager, chairperson, president, etc., where an organizational unit can have only one boss, and one person can be boss of only one organizational unit. If those rules apply, then you have a 1:1 relationship, such as one manager of a department, one CEO of a company, etc. "Boss" relationships don't only apply to people. The same kind of relationship occurs if there is only one store as the headquarters of a company, or if only one city is the capital of a country, for example.
Some kinds of scarce resource allocation, e.g. one employee can be assigned only one company car at a time (e.g. one truck per trucker, one taxi per cab driver, etc.). A colleague gave me this example recently.
Marriage (at least in legal jurisdictions where polygamy is illegal): one person can be married to only one other person at a time. I got this example from a textbook that used this as an example of a 1:1 unary relationship when a company records marriages between its employees.
Matching reservations: when a unique reservation is made and then fulfilled as two separate entities. For example, a car rental system might record a reservation in one entity, and then an actual rental in a separate entity. Although such a situation could alternatively be designed as one entity, it might make sense to separate the entities since not all reservations are fulfilled, and not all rentals require reservations, and both situations are very common.
I repeat the caveat I made earlier that most of these are 1:1 relationships only if no historical information is recorded. So, if an employee changes their role in an organization, or a manager takes responsibility of a different department, or an employee is reassigned a vehicle, or someone is widowed and remarries, then the relationship participants can change. If the database does not store any previous history about these 1:1 relationships, then they remain legitimate 1:1 relationships. But if the database records historical information (such as adding start and end dates for each relationship), then they pretty much all turn into M:M relationships.
There are two notable exceptions to the historical note: First, some relationships change so rarely that historical information would normally not be stored. For example, most IS-A relationships (e.g. product type) are immutable; that is, they can never change. Thus, the historical record point is moot; these would always be implemented as natural 1:1 relationships. Second, the reservation-rental relationship store dates separately, since the reservation and the rental are independent events, each with their own dates. Since the entities have their own dates, rather than the 1:1 relationship itself having a start date, these would remain as 1:1 relationships even though historical information is stored.
Your question can be interpreted in several ways, because of the way you worded it. The responses show this.
There can definitely be 1:1 relationships between data items in the real world. No question about it. The "is a" relationship is generally one to one. A car is a vehicle.
One car is one vehicle. One vehicle might be one car. Some vehicles are trucks, in which case one vehicle is not a car. Several answers address this interpretation.
But I think what you really are asking is... when 1:1 relationships exist, should tables ever be split? In other words, should you ever have two tables that contain exactly the same keys? In practice, most of us analyze only primary keys, and not other candidate keys, but that question is slightly diferent.
Normalization rules for 1NF, 2NF, and 3NF never require decomposing (splitting) a table into two tables with the same primary key. I haven't worked out whether putting a schema in BCNF, 4NF, or 5NF can ever result in two tables with the same keys. Off the top of my head, I'm going to guess that the answer is no.
There is a level of normalization called 6NF. The normalization rule for 6NF can definitely result in two tables with the same primary key. 6NF has the advantage over 5NF that NULLS can be completely avoided. This is important to some, but not all, database designers. I've never bothered to put a schema into 6NF.
In 6NF missing data can be represent by an omitted row, instead of a row with a NULL in some column.
There are reasons other than normalization for splitting tables. Sometimes split tables result in better performance. With some database engines, you can get the same performance benefits by partitioning the table instead of actually splitting it. This can have the advantage of keeping the logical design easy to understand, while giving the database engine the tools needed to speed things up.
I use them primarily for a few reasons. One is significant difference in rate of data change. Some of my tables may have audit trails where I track previous versions of records, if I only care to track previous versions of 5 out of 10 columns splitting those 5 columns onto a separate table with an audit trail mechanism on it is more efficient. Also, I may have records (say for an accounting app) that are write only. You can not change the dollar amounts, or the account they were for, if you made a mistake then you need to make a corresponding record to write adjust off the incorrect record, then create a correction entry. I have constraints on the table enforcing the fact that they cannot be updated or deleted, but I may have a couple of attributes for that object that are malleable, those are kept in a separate table without the restriction on modification. Another time I do this is in medical record applications. There is data related to a visit that cannot be changed once it is signed off on, and other data related to a visit that can be changed after signoff. In that case I will split the data and put a trigger on the locked table rejecting updates to the locked table when signed off, but allowing updates to the data the doctor is not signing off on.
Another poster commented on 1:1 not being normalized, I would disagree with that in some situations, especially subtyping. Say I have an employee table and the primary key is their SSN (it's an example, let's save the debate on whether this is a good key or not for another thread). The employees can be of different types, say temporary or permanent and if they are permanent they have more fields to be filled out, like office phone number, which should only be not null if the type = 'Permanent'. In a 3rd normal form database the column should depend only on the key, meaning the employee, but it actually depends on employee and type, so a 1:1 relationship is perfectly normal, and desirable in this case. It also prevents overly sparse tables, if I have 10 columns that are normally filled, but 20 additional columns only for certain types.
The most common scenario I can think of is when you have BLOB's. Let's say you want to store large images in a database (typically, not the best way to store them, but sometimes the constraints make it more convenient). You would typically want the blob to be in a separate table to improve lookups of the non-blob data.
In terms of pure science, yes, they are useless.
In real databases it's sometimes useful to keep a rarely used field in a separate table: to speed up queries using this and only this field; to avoid locks, etc.
Rather than using views to restrict access to fields, it sometimes makes sense to keep restricted fields in a separate table to which only certain users have access.
I can also think of situations where you have an OO model in which you use inheritance, and the inheritance tree has to be persisted to the DB.
For instance, you have a class Bird and Fish which both inherit from Animal.
In your DB you could have an 'Animal' table, which contains the common fields of the Animal class, and the Animal table has a one-to-one relationship with the Bird table, and a one-to-one relationship with the Fish table.
In this case, you don't have to have one Animal table which contains a lot of nullable columns to hold the Bird and Fish-properties, where all columns that contain Fish-data are set to NULL when the record represents a bird.
Instead, you have a record in the Birds-table that has a one-to-one relationship with the record in the Animal table.
1-1 relationships are also necessary if you have too much information. There is a record size limitation on each record in the table. Sometimes tables are split in two (with the most commonly queried information in the main table) just so that the record size will not be too large. Databases are also more efficient in querying if the tables are narrow.
In SQL it is impossible to enforce a 1:1 relationship between two tables that is mandatory on both sides (unless the tables are read-only). For most practical purposes a "1:1" relationship in SQL really means 1:0|1.
The inability to support mandatory cardinality in referential constraints is one of SQL's serious limitations. "Deferrable" constraints don't really count because they are just a way of saying the constraint is not enforced some of the time.
It's also a way to extend a table which is already in production with less (perceived) risk than a "real" database change. Seeing a 1:1 relationship in a legacy system is often a good indicator that fields were added after the initial design.
Most of the time, designs are thought to be 1:1 until someone asks "well, why can't it be 1:many"? Divorcing the concepts from one another prematurely is done in anticipation of this common scenario. Person and Address don't bind so tightly. A lot of people have multiple addresses. And so on...
Usually two separate object spaces imply that one or both can be multiplied (x:many). If two objects were truly, truly 1:1, even philosophically, then it's more of an is-relationship. These two "objects" are actually parts of one whole object.
If you're using the data with one of the popular ORMs, you might want to break up a table into multiple tables to match your Object Hierarchy.
I have found that when I do a 1:1 relationship its totally for a systemic reason, not a relational reason.
For instance, I've found that putting the reserved aspects of a user in 1 table and putting the user editable fields of the user in a different table allows logically writing those rules about permissions on those fields much much easier.
But you are correct, in theory, 1:1 relationships are completely contrived, and are almost a phenomenon. However logically it allows the programs and optimizations abstracting the database easier.
extended information that is only needed in certain scenarios. in legacy applications and programming languages (such as RPG) where the programs are compiled over the tables (so if the table changes you have to recompile the program(s)). Tag along files can also be useful in cases where you have to worry about table size.
Most frequently it is more of a physical than logical construction. It is commonly used to vertically partition a table to take advantage of splitting I/O across physical devices or other query optimizations associated with segregating less frequently accessed data or data that needs to be kept more secure than the rest of the attributes on the same object (SSN, Salary, etc).
The only logical consideration that prescribes a 1-1 relationship is when certain attributes only apply to some of the entities. However, in most cases there is a better/more normalized way to model the data through entity extraction.
The best reason I can see for a 1:1 relationship is a SuperType SubType of database design. I created a Real Estate MLS data structure based on this model. There were five different data feeds; Residential, Commercial, MultiFamily, Hotels & Land.
I created a SuperType called property that contained data that was common to each of the five separate data feeds. This allowed for very fast "simple" searches across all datatypes.
I create five separate SubTypes that stored the unique data elements for each of the five data feeds. Each SuperType record had a 1:1 relationship to the appropriate SubType record.
If a customer wanted a detailed search they had to select a Super-Sub type for example PropertyResidential.
In my opinion a 1:1 relationship maps a class Inheritance on a RDBMS.
There is a table A that contains the common attributes, i.e. the partent class status
Each inherited class status is mapped on the RDBMS with a table B with a 1:1 relationship
to A table, containing the specialized attributes.
The table namend A contain also a "type" field that represents the "casting" functionality
Bye
Mario
You can create a one to one relationship table if there is any significant performance benefit. You can put the rarely used fields into separate table.
1:1 relationships don't really make sense if you're into normalization as anything that would be 1:1 would be kept in the same table.
In the real world though, it's often different. You may want to break your data up to match your applications interface.
Possibly if you have some kind of typed objects in your database.
Say in a table, T1, you have the columns C1, C2, C3… with a one to one relation. It's OK, it's in normalized form. Now say in a table T2, you have columns C1, C2, C3, … (the names may differ, but say the types and the role is the same) with a one to one relation too. It's OK for T2 for the same reasons as with T1.
In this case however, I see a fit for a separate table T3, holding C1, C2, C3… and a one to one relation from T1 to T3 and from T2 to T3. I even more see a fit if there exist another table, with which there already exist a one to multiple C1, C2, C3… say from table A to multiple rows in table B. Then, instead of T3, you use B, and have a one to one relation from T1 to B, the same for from T2 to B, and still the same one to multiple relation from A to B.
I believe normalization do not agree with this, and that may be an idea outside of it: identifying object types and move objects of a same type to their own storage pool, using a one to one relation from some tables, and a one to multiple relation from some other tables.
It is unnecessary great for security purposes but there better ways to perform security checks. Imagine, you create a key that can only open one door. If the key can open any other door, you should ring the alarm. In essence, you can have "CitizenTable" and "VotingTable". Citizen One vote for Candidate One which is stored in the Voting Table. If citizen one appear in the voting table again, then their should be an alarm. Be advice, this is a one to one relationship because we not refering to the candidate field, we are refering to the voting table and the citizen table.
Example:
Citizen Table
id = 1, citizen_name = "EvryBod"
id = 2, citizen_name = "Lesly"
id = 3, citizen_name = "Wasserman"
Candidate Table
id = 1, citizen_id = 1, candidate_name = "Bern Nie"
id = 2, citizen_id = 2, candidate_name = "Bern Nie"
id = 3, citizen_id = 3, candidate_name = "Hill Arry"
Then, if we see the voting table as so:
Voting Table
id = 1, citizen_id = 1, candidate_name = "Bern Nie"
id = 2, citizen_id = 2, candidate_name = "Bern Nie"
id = 3, citizen_id = 3, candidate_name = "Hill Arry"
id = 4, citizen_id = 3, candidate_name = "Hill Arry"
id = 5, citizen_id = 3, candidate_name = "Hill Arry"
We could say that citizen number 3 is a liar pants on fire who cheated Bern Nie. Just an example.
When you are dealing with a database from a third party product, then you probably don't want to alter their database as to prevent tight coupling. but you may have data that corresponds 1:1 with their data
Anywhere were two entirely independent entities share a one-to-one relationship. There must be lots of examples:
person <-> dentist (its 1:N, so its wrong!)
person <-> doctor (its 1:N, so it's also wrong!)
person <-> spouse (its 1:0|1, so its mostly wrong!)
EDIT: Yes, those were pretty bad examples, particularly if I was always looking for a 1:1, not a 0 or 1 on either side. I guess my brain was mis-firing :-)
So, I'll try again. It turns out, after a bit of thought, that the only way you can have two separate entities that must (as far as the software goes) be together all of the time is for them to exist together in higher categorization. Then, if and only if you fall into a lower decomposition, the things are and should be separate, but at the higher level they can't live without each other. Context, then is the key.
For a medical database you may want to store different information about specific regions of the body, keeping them as a separate entity. In that case, a patient has just one head, and they need to have it, or they are not a patient. (They also have one heart, and a number of other necessary single organs). If you're interested in tracking surgeries for example, then each region should be a unique separate entity.
In a production/inventory system, if you're tracking the assembly of vehicles, then you certainly want to watch the engine progress differently from the car body, yet there is a one to one relationship. A care must have an engine, and only one (or it wouldn't be a 'car' anymore). An engine belongs to only one car.
In each case you could produce the separate entities as one big record, but given the level of decomposition, that would be wrong. They are, in these specific contexts, truly independent entities, although they might not appear so at a higher level.
Paul.