Thread: Database designpattern - product feature
Hi, I'm new
I've been working as the sole administrator of various postgresql projects for a while now. All of which where django projects.
Since a new project is starting and we've found the need for a more generic approach I would like to ask a few questions.
I would like to implement a pattern similar to the product feature pattern explained in the silverstone book - the data model resource book vol 1. It is simply explained. There is a Table PRODUCT holding the fields all the products share, then there is the table PRODUCT_FEATURE, both of them in a “many to many“ relationship.
PRODUCT <--- m -------- n ---> PRODUCT_FEATURE (a table in between of course)
PRODUCT_FEATURE --> PF
PRODUCT --> P
TABLE IN BETWEEN --> TIB
PF defines the feature Type while P stands for the product the feature is applied to. Some of these PF can have values of different types (text, numbers, floating, blob, ...) which would be applied to TIB.
I don't like the idea of having numerous empty fields prepared in TIB, just to store occasional values of different types, therefore I need to specialize those TIB Values.
Now how would I do That?
I could create some tables solely for the means of holding [NUM], [TEXT], [BLOB], [ETC] and reference them with the TIB PK. When using them I could create a view TIBV containing all of [NUM, TEXT, BLOB, ETC] in the same column called Value, and join it with TIB to get the value of a PF.
But is this a good idea?
Is there a better way?
Also, I would have to create a pivot table in order to list all the products with all the features. As this is implemented in C (afaik) I suppose it is rather fast or at least fast enough, but I do not actually know. What I know is, there are about 30 Product Types and around 50 possible product features. One product can have up to approximately 25 PF but are mostly around 5 to 10.
Do you think a pivot table is a good idea?
What alternative do i have?
There is room for caching since the dataset is not updated too often.
regards, adrian
What about keeping all the dynamic columns of each product in a json(b) column ?
Maybe you can make constraints that check the product_type and json->field->type ?On Mon, Jun 1, 2015 at 4:35 PM, Adrian Stern <adrian.stern@unchained.ch> wrote:
Hi, I'm newI've been working as the sole administrator of various postgresql projects for a while now. All of which where django projects.Since a new project is starting and we've found the need for a more generic approach I would like to ask a few questions.I would like to implement a pattern similar to the product feature pattern explained in the silverstone book - the data model resource book vol 1. It is simply explained. There is a Table PRODUCT holding the fields all the products share, then there is the table PRODUCT_FEATURE, both of them in a “many to many“ relationship.PRODUCT <--- m -------- n ---> PRODUCT_FEATURE (a table in between of course)PRODUCT_FEATURE --> PFPRODUCT --> PTABLE IN BETWEEN --> TIBPF defines the feature Type while P stands for the product the feature is applied to. Some of these PF can have values of different types (text, numbers, floating, blob, ...) which would be applied to TIB.I don't like the idea of having numerous empty fields prepared in TIB, just to store occasional values of different types, therefore I need to specialize those TIB Values.Now how would I do That?I could create some tables solely for the means of holding [NUM], [TEXT], [BLOB], [ETC] and reference them with the TIB PK. When using them I could create a view TIBV containing all of [NUM, TEXT, BLOB, ETC] in the same column called Value, and join it with TIB to get the value of a PF.But is this a good idea?Is there a better way?Also, I would have to create a pivot table in order to list all the products with all the features. As this is implemented in C (afaik) I suppose it is rather fast or at least fast enough, but I do not actually know. What I know is, there are about 30 Product Types and around 50 possible product features. One product can have up to approximately 25 PF but are mostly around 5 to 10.Do you think a pivot table is a good idea?What alternative do i have?There is room for caching since the dataset is not updated too often.regards, adrian
Please do reply-all so you also reply to the list.
It's not ~good to develop with sqlite and deploy on posgresql. You should have your 'dev' as close to 'prod' as possible.On Tue, Jun 2, 2015 at 11:44 AM, Adrian Stern <adrian.stern@unchained.ch> wrote:
Database changeability is not a requirement. It just comes with django and makes development so much easier since I can develop on sqlite and deploy the wherever I want. Django orm is not "great" I agree, but it certainly does not suck, there are alternatives like sqlalchemy which are far more powerful.But yea. I get what you're trying to tell me. And I agree, this postgresql feature for jsonb look really nice. Much more easy to use than the whole xquery stuff. The complete EAV Pattern described on wikipedia is actually pretty complex and seems not easy at all to implement in using django. Therefore, i maybe should run a few tests with the json plugins.So let my sketch another approach.PRODUCT -> P- name- type- features (jsonb)PRODUCT_FEATURE -> PF- name- description- datatype- validationP now has the features field of type jsonb, which allows keys specified in PF together with a value of "datatype" or simply a valid one. PF holds the key-name, its datatype for generating the GUI, and some validation pattern for input sanitizing. There is no relation between the Tables.Getting the description is not an issue. I could even create a view mapping the jsonb keys to rows.Yes I like your approach. Is there anything I should be aware of? Some do's and don'ts or known pitfalls?
Sorry. Will do in the future.
Product_freature is a table describing the valid keys for product features. With this it is possible to limit keys to specific groups of products.
On Tue, Jun 2, 2015 at 12:58 PM, Dorian Hoxha <dorian.hoxha@gmail.com> wrote:
Product_feature is another table in this case ?Please do reply-all so you also reply to the list.It's not ~good to develop with sqlite and deploy on posgresql. You should have your 'dev' as close to 'prod' as possible.On Tue, Jun 2, 2015 at 11:44 AM, Adrian Stern <adrian.stern@unchained.ch> wrote:Database changeability is not a requirement. It just comes with django and makes development so much easier since I can develop on sqlite and deploy the wherever I want. Django orm is not "great" I agree, but it certainly does not suck, there are alternatives like sqlalchemy which are far more powerful.But yea. I get what you're trying to tell me. And I agree, this postgresql feature for jsonb look really nice. Much more easy to use than the whole xquery stuff. The complete EAV Pattern described on wikipedia is actually pretty complex and seems not easy at all to implement in using django. Therefore, i maybe should run a few tests with the json plugins.So let my sketch another approach.PRODUCT -> P- name- type- features (jsonb)PRODUCT_FEATURE -> PF- name- description- datatype- validationP now has the features field of type jsonb, which allows keys specified in PF together with a value of "datatype" or simply a valid one. PF holds the key-name, its datatype for generating the GUI, and some validation pattern for input sanitizing. There is no relation between the Tables.Getting the description is not an issue. I could even create a view mapping the jsonb keys to rows.Yes I like your approach. Is there anything I should be aware of? Some do's and don'ts or known pitfalls?
So product_feature is only 1 row for each product_type, right ? Looks good.
On Tue, Jun 2, 2015 at 1:15 PM, Adrian Stern <adrian.stern@unchained.ch> wrote:
Sorry. Will do in the future.Product_freature is a table describing the valid keys for product features. With this it is possible to limit keys to specific groups of products.On Tue, Jun 2, 2015 at 12:58 PM, Dorian Hoxha <dorian.hoxha@gmail.com> wrote:Product_feature is another table in this case ?Please do reply-all so you also reply to the list.It's not ~good to develop with sqlite and deploy on posgresql. You should have your 'dev' as close to 'prod' as possible.On Tue, Jun 2, 2015 at 11:44 AM, Adrian Stern <adrian.stern@unchained.ch> wrote:Database changeability is not a requirement. It just comes with django and makes development so much easier since I can develop on sqlite and deploy the wherever I want. Django orm is not "great" I agree, but it certainly does not suck, there are alternatives like sqlalchemy which are far more powerful.But yea. I get what you're trying to tell me. And I agree, this postgresql feature for jsonb look really nice. Much more easy to use than the whole xquery stuff. The complete EAV Pattern described on wikipedia is actually pretty complex and seems not easy at all to implement in using django. Therefore, i maybe should run a few tests with the json plugins.So let my sketch another approach.PRODUCT -> P- name- type- features (jsonb)PRODUCT_FEATURE -> PF- name- description- datatype- validationP now has the features field of type jsonb, which allows keys specified in PF together with a value of "datatype" or simply a valid one. PF holds the key-name, its datatype for generating the GUI, and some validation pattern for input sanitizing. There is no relation between the Tables.Getting the description is not an issue. I could even create a view mapping the jsonb keys to rows.Yes I like your approach. Is there anything I should be aware of? Some do's and don'ts or known pitfalls?
Hello Adrian,
May I ask why you need a non-standard model? By standard models I mean the following:
1) When you don't need to have subclass specific database constraints: All subclasses in the same table, subclasses that do not have an attribute have that column null. This has the best performance because no joins are required when querying both superclass and subclass attributes, and all the data for an object will be in the same block on disk. The disadvantage of this is that you cannot enforce constraints, such as not-null, on subclass specific attributes columns because the constraints would also be applied to the superclasses. If you can ensure that your application is the only way data can be inserted those constraints will naturally be enforced there.
2) When you need subclass specific database constraints: Use an ORM such as Django's ORM or SQLAlchemy which has one table with the superclass attributes and a table for each subclass with their subclass specific attributes. This is slower because joins will be needed and the data for an object will be in 2 different blocks of disk but it allows you to enforce constraints within the database which will be checked whenever any application tries to insert values. There is a lot of complexity added because there will be so many small tables and indexes but the ORM takes care of that for you.
Will J. Dunn
On Mon, Jun 1, 2015 at 10:35 AM, Adrian Stern <adrian.stern@unchained.ch> wrote:
Hi, I'm newI've been working as the sole administrator of various postgresql projects for a while now. All of which where django projects.Since a new project is starting and we've found the need for a more generic approach I would like to ask a few questions.I would like to implement a pattern similar to the product feature pattern explained in the silverstone book - the data model resource book vol 1. It is simply explained. There is a Table PRODUCT holding the fields all the products share, then there is the table PRODUCT_FEATURE, both of them in a “many to many“ relationship.PRODUCT <--- m -------- n ---> PRODUCT_FEATURE (a table in between of course)PRODUCT_FEATURE --> PFPRODUCT --> PTABLE IN BETWEEN --> TIBPF defines the feature Type while P stands for the product the feature is applied to. Some of these PF can have values of different types (text, numbers, floating, blob, ...) which would be applied to TIB.I don't like the idea of having numerous empty fields prepared in TIB, just to store occasional values of different types, therefore I need to specialize those TIB Values.Now how would I do That?I could create some tables solely for the means of holding [NUM], [TEXT], [BLOB], [ETC] and reference them with the TIB PK. When using them I could create a view TIBV containing all of [NUM, TEXT, BLOB, ETC] in the same column called Value, and join it with TIB to get the value of a PF.But is this a good idea?Is there a better way?Also, I would have to create a pivot table in order to list all the products with all the features. As this is implemented in C (afaik) I suppose it is rather fast or at least fast enough, but I do not actually know. What I know is, there are about 30 Product Types and around 50 possible product features. One product can have up to approximately 25 PF but are mostly around 5 to 10.Do you think a pivot table is a good idea?What alternative do i have?There is room for caching since the dataset is not updated too often.regards, adrian
Hi William, thanks for joining the conversation.
1) We do hope for constraints since a connection to an ERP system is possible in the future. We want to plan ahead.
2) As for the subclass approach: I would need about 30 subclasses and it will get really hard to add new products since a change in the database will be necessary each time. That's why we want a more generic approach.
Maybe I don't understand you right, because of the language barrier. Can you provide me a link to a subclassing example?
ORM is a given in my case. This is not a high performance application.
On Tue, Jun 2, 2015 at 5:35 PM, William Dunn <dunnwjr@gmail.com> wrote:
Hello Adrian,May I ask why you need a non-standard model? By standard models I mean the following:1) When you don't need to have subclass specific database constraints: All subclasses in the same table, subclasses that do not have an attribute have that column null. This has the best performance because no joins are required when querying both superclass and subclass attributes, and all the data for an object will be in the same block on disk. The disadvantage of this is that you cannot enforce constraints, such as not-null, on subclass specific attributes columns because the constraints would also be applied to the superclasses. If you can ensure that your application is the only way data can be inserted those constraints will naturally be enforced there.2) When you need subclass specific database constraints: Use an ORM such as Django's ORM or SQLAlchemy which has one table with the superclass attributes and a table for each subclass with their subclass specific attributes. This is slower because joins will be needed and the data for an object will be in 2 different blocks of disk but it allows you to enforce constraints within the database which will be checked whenever any application tries to insert values. There is a lot of complexity added because there will be so many small tables and indexes but the ORM takes care of that for you.Will J. DunnOn Mon, Jun 1, 2015 at 10:35 AM, Adrian Stern <adrian.stern@unchained.ch> wrote:Hi, I'm newI've been working as the sole administrator of various postgresql projects for a while now. All of which where django projects.Since a new project is starting and we've found the need for a more generic approach I would like to ask a few questions.I would like to implement a pattern similar to the product feature pattern explained in the silverstone book - the data model resource book vol 1. It is simply explained. There is a Table PRODUCT holding the fields all the products share, then there is the table PRODUCT_FEATURE, both of them in a “many to many“ relationship.PRODUCT <--- m -------- n ---> PRODUCT_FEATURE (a table in between of course)PRODUCT_FEATURE --> PFPRODUCT --> PTABLE IN BETWEEN --> TIBPF defines the feature Type while P stands for the product the feature is applied to. Some of these PF can have values of different types (text, numbers, floating, blob, ...) which would be applied to TIB.I don't like the idea of having numerous empty fields prepared in TIB, just to store occasional values of different types, therefore I need to specialize those TIB Values.Now how would I do That?I could create some tables solely for the means of holding [NUM], [TEXT], [BLOB], [ETC] and reference them with the TIB PK. When using them I could create a view TIBV containing all of [NUM, TEXT, BLOB, ETC] in the same column called Value, and join it with TIB to get the value of a PF.But is this a good idea?Is there a better way?Also, I would have to create a pivot table in order to list all the products with all the features. As this is implemented in C (afaik) I suppose it is rather fast or at least fast enough, but I do not actually know. What I know is, there are about 30 Product Types and around 50 possible product features. One product can have up to approximately 25 PF but are mostly around 5 to 10.Do you think a pivot table is a good idea?What alternative do i have?There is room for caching since the dataset is not updated too often.regards, adrian
Sent from my iPad
I don't understand 'ORM is a given' in conjunction with a reluctance to db evolution? These seem oxymoronic.Hi William, thanks for joining the conversation.1) We do hope for constraints since a connection to an ERP system is possible in the future. We want to plan ahead.2) As for the subclass approach: I would need about 30 subclasses and it will get really hard to add new products since a change in the database will be necessary each time. That's why we want a more generic approach.Maybe I don't understand you right, because of the language barrier. Can you provide me a link to a subclassing example?ORM is a given in my case. This is not a high performance application.Freundliche Grüsse
On 6/3/2015 2:50 AM, Adrian Stern wrote:
Hi William, thanks for joining the conversation.1) We do hope for constraints since a connection to an ERP system is possible in the future. We want to plan ahead.2) As for the subclass approach: I would need about 30 subclasses and it will get really hard to add new products since a change in the database will be necessary each time. That's why we want a more generic approach.
At the root of your description it appears to me that you are choosing essentially an EAV design pattern. Constraints and case specific validation become difficult (or impossible) to consistently enforce. I have personal experience in cleaning up a system that used this *exact* pattern (product -> product attribute). Different developers approached updating information in different ways. They also chose to store the attributes as text to avoid the text vs number issue. However, they failed to force any validation and any hint of attempting to prevent duplicates. That destroyed hope of supporting an underlying business need to search for specific values during data analysis. (think of how many different ways you can misspell "poughkeepsie" - but hey... it's "just a name")
I inherited the results of poor development controls and poor control over the weakness of the design - e.g. validation... and the cleanup has been long, and painful.
I think you should evaluate your unease with having to update the database on release (potentially many times) carefully for what it is and why you have it. [I'm not saying it is invalid - just know why you have it] Because no matter how well you design your system - databases evolve. Manage that.
Anybody can muck up part of a project and cause garbage - but speaking from experience... this design pattern really encourages it. If you choose to use it - then you HAVE to control where and when inserts/updates are done and be very careful with specifying how validation is to be done to the entire development team (and potentially the users)... and then review the code (and/or data) regularly.
wide tables/sparse fill on the columns ... I haven't tried to calculate the overhead on this... but disk space is generally considered to be cheap. [that doesn't mean your case wouldn't be criminally wasteful] Choosing 1 wide table or 30 sub-tables to deal with detail data. I don't know how that directly effects Postgres' performance.... if you choose 30 tables ... meh... at least you'll know exactly where your data is - and exactly what is allowed for each and every variant. Remember to enforce a consistent guessable naming convention.
All that said - there are reasons to use this pattern to gain the power of the dynamically expandable configuration of allowed values. I just see the use cases where the gain (flexibility) is worth the pain (validation control) to be few and far between.
just my $0.01
Roxanne
Maybe I don't understand you right, because of the language barrier. Can you provide me a link to a subclassing example?ORM is a given in my case. This is not a high performance application.On Tue, Jun 2, 2015 at 5:35 PM, William Dunn <dunnwjr@gmail.com> wrote:Hello Adrian,May I ask why you need a non-standard model? By standard models I mean the following:1) When you don't need to have subclass specific database constraints: All subclasses in the same table, subclasses that do not have an attribute have that column null. This has the best performance because no joins are required when querying both superclass and subclass attributes, and all the data for an object will be in the same block on disk. The disadvantage of this is that you cannot enforce constraints, such as not-null, on subclass specific attributes columns because the constraints would also be applied to the superclasses. If you can ensure that your application is the only way data can be inserted those constraints will naturally be enforced there.2) When you need subclass specific database constraints: Use an ORM such as Django's ORM or SQLAlchemy which has one table with the superclass attributes and a table for each subclass with their subclass specific attributes. This is slower because joins will be needed and the data for an object will be in 2 different blocks of disk but it allows you to enforce constraints within the database which will be checked whenever any application tries to insert values. There is a lot of complexity added because there will be so many small tables and indexes but the ORM takes care of that for you.Will J. DunnOn Mon, Jun 1, 2015 at 10:35 AM, Adrian Stern <adrian.stern@unchained.ch> wrote:Hi, I'm newI've been working as the sole administrator of various postgresql projects for a while now. All of which where django projects.Since a new project is starting and we've found the need for a more generic approach I would like to ask a few questions.I would like to implement a pattern similar to the product feature pattern explained in the silverstone book - the data model resource book vol 1. It is simply explained. There is a Table PRODUCT holding the fields all the products share, then there is the table PRODUCT_FEATURE, both of them in a “many to many“ relationship.PRODUCT <--- m -------- n ---> PRODUCT_FEATURE (a table in between of course)PRODUCT_FEATURE --> PFPRODUCT --> PTABLE IN BETWEEN --> TIBPF defines the feature Type while P stands for the product the feature is applied to. Some of these PF can have values of different types (text, numbers, floating, blob, ...) which would be applied to TIB.I don't like the idea of having numerous empty fields prepared in TIB, just to store occasional values of different types, therefore I need to specialize those TIB Values.Now how would I do That?I could create some tables solely for the means of holding [NUM], [TEXT], [BLOB], [ETC] and reference them with the TIB PK. When using them I could create a view TIBV containing all of [NUM, TEXT, BLOB, ETC] in the same column called Value, and join it with TIB to get the value of a PF.But is this a good idea?Is there a better way?Also, I would have to create a pivot table in order to list all the products with all the features. As this is implemented in C (afaik) I suppose it is rather fast or at least fast enough, but I do not actually know. What I know is, there are about 30 Product Types and around 50 possible product features. One product can have up to approximately 25 PF but are mostly around 5 to 10.Do you think a pivot table is a good idea?What alternative do i have?There is room for caching since the dataset is not updated too often.regards, adrian
-- [At other schools] I think the most common fault in general is to teach students how to pass exams instead of teaching them the science. Donald Knuth
On June 3, 2015 02:04:28 PM Roxanne Reid-Bennett wrote: > I think you should evaluate your unease with having to update the database > on release (potentially many times) carefully for what it is and why you > have it. [I'm not saying it is invalid - just know why you have it] > Because no matter how well you design your system - databases evolve. > Manage that. Having been guilty of designing an EAV system before, I think I know his hesitation is due to the fact that some databases (*cough* Oracle *cough*) don't allow DDL in transactions (or at least back when I worked with Oracle it didn't), making dynamic table creation a bit of a problem, especially when you run in a container which gives you little flexibility in your tx handling (i.e. you get it all the time, or never). This used to be a problem in many iterations of J2EE containers. Also, lots of DBAs get skittish when they hear about applications doing DDL. And again, many of the technological roadblocks are fixed by now, but the hesitation remains. Combine this with the fact that you want users to be able to create new products, which should be built up out of existing and/or newly defined attributes, you quickly end up with something EAV like. Because you don't want your product management people coming crying to your DBAs to have a new table for a new product defined. You want the product management people to point- and-click their way through a nice GUI. So this is what lead me to that EAV design for this exact problem: we started off with Oracle as the database and a temperamental J2EE container, found out we couldn't do DDL (or at least DDL was hard), and by the time we were on less brain dead containers and databases the "damage" was done and there was no going back. But in my defense I will say that mine was one of the prettiest EAV systems ever built. In my opinion at least :-)
(Sorry Jan for receiving this twice)
Thank you both for your Input. I absolutely see your point against EAV.
I will work out two variants based on the specific solution, where i would create a (bigger) Table for each group of similar products, and based on the dynamic JSON solution.
With this we can have a good discussion about the pros and cons in our next meeting. In the end, the customer hast to decide how important the flexibility is for him. (And yes, the customer has IT-People who will understand why and what we talk about)
So thanks for doubting my approach, it has been helpful!
On Thu, Jun 4, 2015 at 4:02 AM, Jan de Visser <jan@de-visser.net> wrote:
On June 3, 2015 02:04:28 PM Roxanne Reid-Bennett wrote:
> I think you should evaluate your unease with having to update the database
> on release (potentially many times) carefully for what it is and why you
> have it. [I'm not saying it is invalid - just know why you have it]
> Because no matter how well you design your system - databases evolve.
> Manage that.
Having been guilty of designing an EAV system before, I think I know his
hesitation is due to the fact that some databases (*cough* Oracle *cough*)
don't allow DDL in transactions (or at least back when I worked with Oracle it
didn't), making dynamic table creation a bit of a problem, especially when you
run in a container which gives you little flexibility in your tx handling
(i.e. you get it all the time, or never). This used to be a problem in many
iterations of J2EE containers. Also, lots of DBAs get skittish when they hear
about applications doing DDL. And again, many of the technological roadblocks
are fixed by now, but the hesitation remains.
Combine this with the fact that you want users to be able to create new
products, which should be built up out of existing and/or newly defined
attributes, you quickly end up with something EAV like. Because you don't want
your product management people coming crying to your DBAs to have a new table
for a new product defined. You want the product management people to point-
and-click their way through a nice GUI.
So this is what lead me to that EAV design for this exact problem: we started
off with Oracle as the database and a temperamental J2EE container, found out
we couldn't do DDL (or at least DDL was hard), and by the time we were on less
brain dead containers and databases the "damage" was done and there was no
going back.
But in my defense I will say that mine was one of the prettiest EAV systems
ever built. In my opinion at least :-)
--
Sent via pgsql-general mailing list (pgsql-general@postgresql.org)
To make changes to your subscription:
http://www.postgresql.org/mailpref/pgsql-general
Hello Adrian,
Sorry for the late response. I've not used Django so I can't provide specific guidance on how you would implement it with that but in SQLAlchemy that model is called "joined-table-inheritance": http://docs.sqlalchemy.org/en/latest/orm/inheritance.html#joined-table-inheritance
That is also the behavior of Hibernate (Java) when using "table per subclass" mapping.
Will J. Dunn
On Wed, Jun 3, 2015 at 2:50 AM, Adrian Stern <adrian.stern@unchained.ch> wrote:
Hi William, thanks for joining the conversation.1) We do hope for constraints since a connection to an ERP system is possible in the future. We want to plan ahead.2) As for the subclass approach: I would need about 30 subclasses and it will get really hard to add new products since a change in the database will be necessary each time. That's why we want a more generic approach.Maybe I don't understand you right, because of the language barrier. Can you provide me a link to a subclassing example?ORM is a given in my case. This is not a high performance application.On Tue, Jun 2, 2015 at 5:35 PM, William Dunn <dunnwjr@gmail.com> wrote:Hello Adrian,May I ask why you need a non-standard model? By standard models I mean the following:1) When you don't need to have subclass specific database constraints: All subclasses in the same table, subclasses that do not have an attribute have that column null. This has the best performance because no joins are required when querying both superclass and subclass attributes, and all the data for an object will be in the same block on disk. The disadvantage of this is that you cannot enforce constraints, such as not-null, on subclass specific attributes columns because the constraints would also be applied to the superclasses. If you can ensure that your application is the only way data can be inserted those constraints will naturally be enforced there.2) When you need subclass specific database constraints: Use an ORM such as Django's ORM or SQLAlchemy which has one table with the superclass attributes and a table for each subclass with their subclass specific attributes. This is slower because joins will be needed and the data for an object will be in 2 different blocks of disk but it allows you to enforce constraints within the database which will be checked whenever any application tries to insert values. There is a lot of complexity added because there will be so many small tables and indexes but the ORM takes care of that for you.Will J. DunnOn Mon, Jun 1, 2015 at 10:35 AM, Adrian Stern <adrian.stern@unchained.ch> wrote:Hi, I'm newI've been working as the sole administrator of various postgresql projects for a while now. All of which where django projects.Since a new project is starting and we've found the need for a more generic approach I would like to ask a few questions.I would like to implement a pattern similar to the product feature pattern explained in the silverstone book - the data model resource book vol 1. It is simply explained. There is a Table PRODUCT holding the fields all the products share, then there is the table PRODUCT_FEATURE, both of them in a “many to many“ relationship.PRODUCT <--- m -------- n ---> PRODUCT_FEATURE (a table in between of course)PRODUCT_FEATURE --> PFPRODUCT --> PTABLE IN BETWEEN --> TIBPF defines the feature Type while P stands for the product the feature is applied to. Some of these PF can have values of different types (text, numbers, floating, blob, ...) which would be applied to TIB.I don't like the idea of having numerous empty fields prepared in TIB, just to store occasional values of different types, therefore I need to specialize those TIB Values.Now how would I do That?I could create some tables solely for the means of holding [NUM], [TEXT], [BLOB], [ETC] and reference them with the TIB PK. When using them I could create a view TIBV containing all of [NUM, TEXT, BLOB, ETC] in the same column called Value, and join it with TIB to get the value of a PF.But is this a good idea?Is there a better way?Also, I would have to create a pivot table in order to list all the products with all the features. As this is implemented in C (afaik) I suppose it is rather fast or at least fast enough, but I do not actually know. What I know is, there are about 30 Product Types and around 50 possible product features. One product can have up to approximately 25 PF but are mostly around 5 to 10.Do you think a pivot table is a good idea?What alternative do i have?There is room for caching since the dataset is not updated too often.regards, adrian