I have a site that has different type of products with different specifications for each of them.
I want to be able to use only one products table with a set of columns but because columns are different depending on what type, I have to create multiple products table catering for each type. This I think is time consuming and not really effective way to manage as an ongoing solution.
Is there a good way to manage this type of scenario with the database?
I'm using Cakephp as the framework.
Normalise your data structure: for example, have a product_info table (with FK into the products table) that contains columns key and value to express additional information about each product.
Martin Fowler lists three general approaches.
Single table - Putting all the columns in one table and only using the ones you need (this sounds the closest to what you have)
Class table - All classes have their own table storing data specific to that class (with the same primary key in every relevant table)
Concrete table - The same as above, but only concrete classes have tables, not abstract ones.
Single table is the simplest unless you have a good reason not to - just have all possible fields there, and only use the ones you need in each class. You do have the disadvantage of not being able to enforce NOT NULL; if this matters, either make a custom constraint depending on the type of object, or use option 2 or 3.
I wrote about using the EAV model with cake a little while ago, I think this post might be helpful, but slightly outdated.
http://nuts-and-bolts-of-cakephp.com/2010/07/27/keyvalue-tables-and-how-to-use-them-in-cakephp-1-3/
Also, this could be very helpful for your particular question... Please take a look and study some concepts in Magento (a very popular PHP-based ecommerce framework) makes heavy use of EAV schemas and does a nice job of indexing and flattening the data.
You can certainly gain a lot of interesting perspective on EAV implementation. Whether you love it or not is a different story :)
Related
I do not have much experience in table design. My goal is to create one or more product tables that meet the requirements below:
Support many kinds of products (TV, Phone, PC, ...). Each kind of product has a different set of parameters, like:
Phone will have Color, Size, Weight, OS...
PC will have CPU, HDD, RAM...
The set of parameters must be dynamic. You can add or edit any parameter you like.
How can I meet these requirements without a separate table for each kind of product?
You have at least these five options for modeling the type hierarchy you describe:
Single Table Inheritance: one table for all Product types, with enough columns to store all attributes of all types. This means a lot of columns, most of which are NULL on any given row.
Class Table Inheritance: one table for Products, storing attributes common to all product types. Then one table per product type, storing attributes specific to that product type.
Concrete Table Inheritance: no table for common Products attributes. Instead, one table per product type, storing both common product attributes, and product-specific attributes.
Serialized LOB: One table for Products, storing attributes common to all product types. One extra column stores a BLOB of semi-structured data, in XML, YAML, JSON, or some other format. This BLOB allows you to store the attributes specific to each product type. You can use fancy Design Patterns to describe this, such as Facade and Memento. But regardless you have a blob of attributes that can't be easily queried within SQL; you have to fetch the whole blob back to the application and sort it out there.
Entity-Attribute-Value: One table for Products, and one table that pivots attributes to rows, instead of columns. EAV is not a valid design with respect to the relational paradigm, but many people use it anyway. This is the "Properties Pattern" mentioned by another answer. See other questions with the eav tag on StackOverflow for some of the pitfalls.
I have written more about this in a presentation, Extensible Data Modeling.
Additional thoughts about EAV: Although many people seem to favor EAV, I don't. It seems like the most flexible solution, and therefore the best. However, keep in mind the adage TANSTAAFL. Here are some of the disadvantages of EAV:
No way to make a column mandatory (equivalent of NOT NULL).
No way to use SQL data types to validate entries.
No way to ensure that attribute names are spelled consistently.
No way to put a foreign key on the values of any given attribute, e.g. for a lookup table.
Fetching results in a conventional tabular layout is complex and expensive, because to get attributes from multiple rows you need to do JOIN for each attribute.
The degree of flexibility EAV gives you requires sacrifices in other areas, probably making your code as complex (or worse) than it would have been to solve the original problem in a more conventional way.
And in most cases, it's unnecessary to have that degree of flexibility. In the OP's question about product types, it's much simpler to create a table per product type for product-specific attributes, so you have some consistent structure enforced at least for entries of the same product type.
I'd use EAV only if every row must be permitted to potentially have a distinct set of attributes. When you have a finite set of product types, EAV is overkill. Class Table Inheritance would be my first choice.
Update 2019: The more I see people using JSON as a solution for the "many custom attributes" problem, the less I like that solution. It makes queries too complex, even when using special JSON functions to support them. It takes a lot more storage space to store JSON documents, versus storing in normal rows and columns.
Basically, none of these solutions are easy or efficient in a relational database. The whole idea of having "variable attributes" is fundamentally at odds with relational theory.
What it comes down to is that you have to choose one of the solutions based on which is the least bad for your app. Therefore you need to know how you're going to query the data before you choose a database design. There's no way to choose one solution that is "best" because any of the solutions might be best for a given application.
#StoneHeart
I would go here with EAV and MVC all the way.
#Bill Karvin
Here are some of the disadvantages of
EAV:
No way to make a column mandatory (equivalent of NOT NULL).
No way to use SQL data types to validate entries.
No way to ensure that attribute names are spelled consistently.
No way to put a foreign key on the values of any given attribute, e.g.
for a lookup table.
All those things that you have mentioned here:
data validation
attribute names spelling validation
mandatory columns/fields
handling the destruction of dependent attributes
in my opinion don't belong in a database at all because none of databases are capable of handling those interactions and requirements on a proper level as a programming language of an application does.
In my opinion using a database in this way is like using a rock to hammer a nail. You can do it with a rock but aren't you suppose to use a hammer which is more precise and specifically designed for this sort of activity ?
Fetching results in a conventional tabular layout is complex and
expensive, because to get attributes
from multiple rows you need to do JOIN
for each attribute.
This problem can be solved by making few queries on partial data and processing them into tabular layout with your application. Even if you have 600GB of product data you can process it in batches if you require data from every single row in this table.
Going further If you would like to improve the performance of the queries you can select certain operations like for e.g. reporting or global text search and prepare for them index tables which would store required data and would be regenerated periodically, lets say every 30 minutes.
You don't even need to be concerned with the cost of extra data storage because it gets cheaper and cheaper every day.
If you would still be concerned with performance of operations done by the application, you can always use Erlang, C++, Go Language to pre-process the data and later on just process the optimised data further in your main app.
If I use Class Table Inheritance meaning:
one table for Products, storing attributes common to all product types. Then one table per product type, storing attributes specific to that product type.
-Bill Karwin
Which I like the best of Bill Karwin's Suggestions.. I can kind of foresee one drawback, which I will try to explain how to keep from becoming a problem.
What contingency plan should I have in place when an attribute that is only common to 1 type, then becomes common to 2, then 3, etc?
For example: (this is just an example, not my real issue)
If we sell furniture, we might sell chairs, lamps, sofas, TVs, etc. The TV type might be the only type we carry that has a power consumption. So I would put the power_consumption attribute on the tv_type_table. But then we start to carry Home theater systems which also have a power_consumption property. OK its just one other product so I'll add this field to the stereo_type_table as well since that is probably easiest at this point. But over time as we start to carry more and more electronics, we realize that power_consumption is broad enough that it should be in the main_product_table. What should I do now?
Add the field to the main_product_table. Write a script to loop through the electronics and put the correct value from each type_table to the main_product_table. Then drop that column from each type_table.
Now If I was always using the same GetProductData class to interact with the database to pull the product info; then if any changes in code now need refactoring, they should be to that Class only.
You can have a Product table and a separate ProductAdditionInfo table with 3 columns: product ID, additional info name, additional info value. If color is used by many but not all kinds of Products you could have it be a nullable column in the Product table, or just put it in ProductAdditionalInfo.
This approach is not a traditional technique for a relational database, but I have seen it used a lot in practice. It can be flexible and have good performance.
Steve Yegge calls this the Properties pattern and wrote a long post about using it.
I'm developing a stock and warehouse management system using relational databases (MySQL) and PHP. Due to the fact that the stock products will have multiple characteristics (widths, heights, weights, measures, colors, etc) there raises the need of having a database model approach of storing the attributes and the possibility to add/edit new attributes, alter product types and so on.
So, in the current concept I can see only 3 viable models:
store all attributes in a single table, as separated column and
based on product type (probably category) to serve them to the end
user to fill
the EAV (Entity - Attribute - Value) model that will involve
something like this:
a category table containing classes of attributes
a class of attributes table that will contain separate classes with multiple attributes (in this manner we ensure that we can add to a category a class of attributes without the need to manually add to similar categories attributes one after the other)
a attributes table responsible for the attribute itself
a attributes values table where we store the values
Store all common attributes in a single table and create multiple tables for all different category type: this model would require to change the database every time we encounter a new category type
The second model is inspired from here.
After reading a lot regarding the EAV model I now have doubts over this model and I am little concern regarding the ways I will have to connect different product attributes in orders / invoices and so on.. Even the validation of forms seems that it will be a real pain of using the EAV model, but still.. I wouldn't like to have a single table with 100+ columns and then to be ready to add new columns whenever a new attribute is to be added..
So, the question would be: is there a cheaper solution? Or could the EAV model be improved?
I know it's a long and old debate, but everybody is just pointing to NoSQL and I only rely on RDBMS..
EDIT:
The downside of those approaches (or of most of the approaches found) is that:
for a specified attribute there probably should exist a measure unit
(eq. attribute weight should have a drop down with measuring units)
a specified attribute should be mandatory or not
all attributes should have a validation on form submit
Until now, the only feasible solution would be to create a new table for every new category, and deal in that table with all custom attributes and rules. But, yet again, it would end up to a real pain when a new category is to be set up.
EDIT 2:
The option of using a Json column in MySQL, does not solve from my point of view any of the downsides mentioned above.. OR, maybe I am wrong and I don't clearly see the big picture..
I gather that these are your primary requirements:
Flexible attributes
Your exact need here is unclear: it sounds like you either expect the attributes to change, or at least expect that all attributes will not always be applicable to all products (i.e. a sparse matrix)
Products are also categorized, and the category will (at least partially) determine what attributes are applicable to a product
The attributes themselves may have additional properties aside from their value, that must be provided by the user (i.e. a unit that goes with a weight)
Input validation is a must, and checks things like:
All required attributes are present
Attributes which are not applicable are not present
Attributes have valid values
User-provided attribute properties have valid values
You probably also want to make sure you can search/filter efficiently by attributes
These different requirements all result in different technical needs, and different technical solutions. Some are matters of database, and some will have to be solved in code regardless of database choice. Obviously you are aware of some of these issues, but I think it is worth really breaking it down:
Flexible Attributes
Having a list of flexible attributes (as you know) does not work well with RDBMS systems where your table schema has to be pre-defined. This includes pretty much all of the SQLs, and definitely MySQL. The issue is that changing the table schema is expensive and for large tables can take minutes or hours, making it practically impossible to add attributes if you have to add a column to a table to do it.
Even if your list of attributes rarely changes, a large table of attributes is very inefficient if most products don't have a value for most attributes (i.e. a sparse matrix).
In the long run, you just won't get anywhere if your attributes are stored as a column in tables. Even if you break it down per-category, you are still going to have large empty tables that you can't add columns to dynamically.
If you stick with an RDBMS your only option is really an EAV system. Having considered, researched, and implemented EAV systems, I wouldn't worry too much about all the hype you hear about them on the internet. I know that there are lots of articles out there talking about the EAV "anti-pattern", and I'm the kind of person who takes proper use of software design patterns seriously, but EAV does have a perfectly valid time and place, and this is it. In the long run you will not be able to do this on an RDBMS without EAV. You could certainly look at a NoSQL system that is designed for this specific kind of problem, but when the rest of your database is in a standard RDBMS, installing or switching to a NoSQL system just to store your attribute values is almost certainly overkill. You certainly aren't going to want to lose the ACID compliance that a RDMBS comes with, and most NoSQL systems don't guarantee ACID compliance. There is a wave of NewSQL systems out there that are designed to get the best of both worlds, but if this is just one part of a larger application (which I'm sure is the case), it probably isn't worth investigating completely new technologies just to make this one feature happen. You could also consider using something like JSON storage inside MySQL to store your attribute values. That is a viable option now that MySQL has better JSON support, but that only makes a small change to the big picture: you would still need all your other EAV tables to keep track of allowed attributes, categories, etc. It is only the attribute values that you would be able to place inside of the JSON data, so the potential benefits of JSON storage are relatively small (and have other issues that I will mention down the road).
So in summary, I would say that as long as the rest of your application runs on a RDBMS, it is perfectly reasonable to use EAV to manage flexible attributes. If you were trying to build your entire system in an EAV inside of a RDBMS, then you would definitely be wasting your time and I'd tell you to go find a good NoSQL database that fits the problem you are trying to solve. The disadvantages of EAV do still apply though: you can't easily perform consistency checks within your RDBMS system, and will have to do that yourself in code.
Categorized products with category-specific attributes
You've pretty much got it here. This is relatively straight-forward inside an EAV system. You will have your attributes table, you will have a category table, and then you will need a standard one-to-many or many-to-many relationship between the attributes and categories table which will determine which attributes are available to which category. You obviously also have a relationship between products and categories, so you know which products therefore need which attributes.
Your option #3 is designed to fulfill this requirement, but having a table with each attribute as a column will scale very poorly as your system grows, and will definitely break if you ever need to dynamically add attributes. You don't want to be running ALTER TABLE statements on the fly, especially if you have more than a few thousand records.
Managing attribute properties
It is one thing to store dynamic attributes and values. It is another problem entirely to store dynamic attributes, values, and associated meta data (i.e. store a weight as well as the unit the weight is in). This however is no longer a database problem, but rather a code problem. In terms of actually storing the information your best bet is to probably store your meta data inside your attribute values table, and rely upon some code abstractions to handle the input validation as well as form building. That can get quite complicated quite fast, especially if done wrong, and talking through such a system would take another entire post. However, I think you are on the right track: for a fancier attribute that requires both a value and meta data, you need to somehow assign a class that is responsible for input processing and form validation. For instance for a simple text field you have a "text" class that reads the user's value out of the form and stores it in the proper "attribute_values" table, with no meta data stored. Then for your "weight" attribute you would have a "weight" attribute that stores the number given by the user (i.e. 0.5) but then also stores the unit the user specified with that number (i.e. 'lbs') and persists both to the "attribute_values" table (in pseudo-SQL): INSERT INTO attribute_values value='0.5', meta_data='{"unit":"lbs"}', product_id=X, attribute_id=X. Ironically JSON probably would be a good way to store this meta data, since the exact meta data kept will also vary by attribute type, and I doubt you would another level of tables to handle that variation in your EAV tables.
Again, this is more of a code problem than storage problem. If you decided to do JSON tables the overall picture to meet this requirement wouldn't change: your "attribute type classes" would simply store the meta data in a different way. That would probably look something like: UPDATE products SET attributes='{"weight":0.5,"unit":"lbs"}' WHERE id=X
Input Validation
This will have to be handled exclusively by code regardless of how you store your data, so this requirement doesn't matter much in terms of deciding your database structure. A class-based system as described above will also be able to handle input validation, if properly executed.
Sort/Search/Filter
This doesn't matter if you are exclusively using your attributes for data storage/retrieval, but will you be searching on attributes at all? With a proper EAV system and good indexes, you can actually search/sort efficiently in an RDBMS system (although it can start to get painful if you search by more than a handful of indexes at a time). I haven't looked in detail, but I'm pretty sure that using JSON for storage won't scale well when it comes to searching. While MySQL can work with JSON now and search the columns directly, I seriously doubt that such searching/sorting makes use of MySQL indexes, which means that it won't work with large databases. I could be wrong on that one though. It would be worth digging into before committing to a MySQL/JSON storage setup, if you were going to do something like that.
Depending on your needs, this is also a good place to compliment an RDBMS system with a NoSQL system. Having managed large-ish (~1.5 million product) e-commerce systems before, I have found that MySQL tends to fall flat in the searching/sorting category, especially if you are doing any kind of text searching. In an e-commerce system a query like: "Show me the results that best match the term 'blue truck' and have the attribute 'For ages 3-5'" is common, but doing something like that in MySQL is about impossible, primarily because of the need for relevancy based sorting and scoring. We solved this problem by using Apache Solr (Elastic is a similar solution) and it managed our searching/sorting/search term scoring very well. In this case it was a two database solution. MySQL kept all the actual data and stored attributes in EAV tables, and anytime something got updated we pushed a record of everything to Apache Solr for additional storage. When a query came in from a user we would query Apache Solr which was an expert at text searching and could also handle the attribute filtering with no trouble, and then we would pull the full product record out of our MySQL database. The system worked beautifully. We had 1.5 million products, thousands of custom attributes, and had no trouble running the whole thing off of a single virtual server. Obviously there was a lot of code going on behind the scenes, but the point is that it definitely worked and wasn't difficult to maintain. Never had any issues with performance from either MySQL or Solr.
Well, this is just one approach. You could simplify this if you don't need or want all of this.
You could, for example, use a Json column in Mysql, to store all of the extra attributes. Another idea, in the product type, add a json column to store the custom attributes and types, and use this to draw the form on the screen.
I would recommend you to go through an EAV database first in order to understand the database creation & its values.
You can follow magento DB structure which uses EAV model.
EAV stands for Entity attribute and value model. Let’s closely have a look at all parts.
Entity: Data items are represented as entity, it can be a product or customer or a category. In the database each entity have a record.
Attribute: These are belongs to different entity, for example a Customer entity have attributes like Name, Age, Address etc. In Magento database all attributes are listed in a single table.
Value: Simply the values of the attributes, for example for the Name attribute the value will be “Rajat”.
EAV is used when you have many attributes for an entity and these attribute are dynamic (added/removed).
Also there is a high possibility that many of these attribute would have empty or null value most of the time.
In such a situation EAV structure has many advantages mainly with optimized mysql storage
For Your case - Category can also have attributes, products can also have attributes so on with customers etc ...
Let's take an example of categories. Following are the tables provided by magento:
1. catalog_category_entity
2. catalog_category_entity_datetime
3. catalog_category_entity_decimal
4. catalog_category_entity_int
5. catalog_category_entity_text
6. catalog_category_entity_varchar
7. catalog_category_flat
Follow this link to know more about table
Magento Category Tables
For attributes which are select box. You can put dropdown values under option values.
Follow this to link to understand magento eav structure which will give you clear picture about how EAV model work & how you can make a best use of it.
magento table structure
There are three approaches if you want to stick with a relational database.
The first is best if you know in advance the attributes for all the products. You chose one of the three ways to store polymorphic data in a relational model.
It's "clean" from a relational point of view - you're just using rows and columns, but each of the 3 options has its own benefits and drawbacks.
If you don't know your attributes at development time, I'd recommend against these solutions - they'd require significant additional tooling.
The next option is EAV. The benefits and drawbacks are well documented - but your focus on "validating input forms" is only one use case for the data, and I think you could easily find your data becomes "write only". Providing sorting/filtering, for instance, becomes really hard ("find all products with a height of at least 12, and sort by material_type" is almost impossible using the EAV model).
The option I prefer is a combination of relational data for the core, invariant data, and document-centric (JSON/XML) for the variant data.
MySQL can query JSON natively - so you can sort/filter by the variant attributes. You'd have to create your own validation logic, though - perhaps by integrating JSON Schema in your data entry applications.
By using JSON Schema, you can introduce concepts that "belong together", and provide lookup values. For instance, if you have product weight, your schema might say weight always must have a unit of measure, with the valid options being kilogram, milligram, ounce, pound etc.
If you have foreign key relationships in the variant data, you have a problem - for instance, "manufacturer" might link to a manufacturers table. You can either model this as an explicit column, or in the JSON and do without SQL's built-in foreign key tools like joins.
I have this situation where i need suggestions on database tables design.
BACKGROUND
I am developing an application in PHP ( cakephp to be precise ). where we upload an xml file, it parses the file and save data in databases. These XML could be files or url feeds and these are purchased from various suppliers for data. It is intended to collect various venues data from source urls , venues can be anything like hotels , cinemas , schools , restaurants etc.
Problem
Initial table structure for these venues is as below . table is deigned to store generic information initially.
id
Address
Postcode
Lat
Long
SourceURL
Source
Type
Phone
Email
Website
With the more data coming from different sources , I realized that there are many attributes for different types of venues.
For example
a hotel can have some attributes like
price_for_one_day, types_of_accommodation, Number_of_rooms etc
where as schools will not have them but have different set of attributes.Restaurant will have some other attributes.
My first idea is to create two tables called vanue_attribute_names , Venue_attributes
##table venue_attribute_names
_____________________________
id
name
##table venue_attributes
________________________
id
venue_id
venue_attribute_name_id
value
So if I detect any new attribute I want to create one and the its value in attributes table with a relation. But I doubt this is not the correct approach. I believe there could be any other approach for this?. Besides if table grows huge there could be performance issues because of increase in joins and also sql queries
Is creating widest possible table with all possible attributes as columns is right approach? Please let me know. If there any links where I could refer I can follow it . Thanks
This is a surprisingly common problem.
The design you describe is commonly known as "Entity/Attribute/Value" or EAV. It has the benefit of allowing you to store all kinds of data without knowing in advance what the schema for that data is. It has the drawback of being hard to query - imagine finding all hotels in a given location, where the daily roomrate is between $100 and $150, whose name starts with "Waldorf". Writing queries against all the attributes and applying boolean logic quickly becomes harder than you'd want it to be. You also can't easily apply database-level consistency checks like "hotel_name must not be null", or "daily_room_rate must be a number".
If neither of those concerns worry you, maybe your design works.
The second option is to store the "common" fields in a traditional relational structure, but to store the variant data in some kind of document - MySQL supports XML, for instance. That allows you to define an XML schema, and query using XPath etc.
This approach gives you better data integrity than EAV, because you can apply schema constraints. It does mean that you have to create a schema for each type of data you're dealing with. That might be okay for you - I'm guessing that the business doesn't add dozens of new venue types every week.
Performance with XML querying can be tricky, and general tooling and the development approach will make it harder to build than "just SQL".
The final option if you want to stick with a relational database is to simply bite the bullet and use "pure" SQL. You can create a "master" table with the common attributes, and a "restaurant" table with the restaurant-specific attributes, a "hotel" table with the hotel attributes. This works as long as you have a manageable number of venue types, and they don't crop up unpredictably.
Finally, you could look at NoSQL options.
If you are sticking with a relational data base, that's it. The options you listed are pretty much what they can give you.
For your situation MongoDB (or an other document oriented NoSql system) could be a good option. This db systems are very good if your have a lot of records with different atributes.
Currently, I am dealing with database structure and I would like to get a piece of advice.
I have 2 objects: banner and ad.
For them I may create banner table and ad table, which will hold all the info about each entity. As main advantage I see that everything related to 1 entity is in this entity table.
On the other hand, I may some table like:
entity_properties.
It will hold value_id entity_id property value. The main advantage is that for entities I need only some basic fields, other fields can be put in this table.
But I am not sure which is the better practice and performance?
Thanks in advance.
For the sake of normalization it is always better to have 1 table per 1 entity. Normalization is an aim or an approach to minimize redundancy and dependency in relational databases . In your case banner and ad are different entities. For now it seems that you can use them in same table. So "redundancy" is not the case. However, what if you want to add some additional fields later?
In addition code complexity and readability is another issue. For instance, when you add different types of object in same table you need to add an internal logic to differentiate them in your code. This means you have complex and probably less readable code.
That depends on the exact use of your system and the attributes/values you're trying to store.
As I see it, I think it would be good to save the important and required information in one table, your 'ad' table, and the rest in the 'ad_entities' table, with an ad_id, entity_name, entity_value, or something similar for your application.
This is a good performance choice since you'll be able to get all the information about the current Ad or all Ads using just one quite simple query, which your objects can easily figure out.
I have recently started doing freelance PHP + MySQL development in my free time, to supplement my income from a full-time job where I write C#/SQL Server code. One of the big database-related differences I've noticed is that MySQL has an enum datatype, whereas SQL Server does not.
When I noticed the enum datatype, I immediately decided to flatten my data model in favor of having a big table that makes use of enumerations rather than many smaller tables for discrete entities and one big "bridge" sort of table.
The website I'm currently working on is for a record label. I only have one table to store the releases for the label, the "releases" table. I have used enumerations everywhere I would normally use a foreign key to a separate table--Artist name, Label name, and several others. The user has the ability to edit these enumeration columns through the backend. The major advantage I see for enumerations over using a text field for this is that artist names will be reused, which should improve data integrity. I also see an advantage in having fewer tables in the database.
Incidentally, I do still have one additional table and a bridge table--there is a "Tags" feature to add tags to a particular release, and since this is a many-to-many relationship, I feel a discrete tag table and a bridge table to join tags to releases is appropriate
Having never encountered an ENUM datatype in a database before, I wonder if I am making wise use of this feature, or if there are problems I haven't foreseen that might come back to bite me as a result of this data architecture. Experienced MySQL'ers, what do you think?
In short, this is not a good design. Foreign keys have a purpose.
From the documentation for the ENUM type:
An enumeration can have a maximum of 65,535 elements.
Your design will not allow you to store more than 65k distinct artist names.
Have you considered what happens when you add a new artist name? I assume you are running an ALTER TABLE to add new enum types? According to a similar SO question this is a very expensive operation. Contrast this with the cost of simply adding another row to the artist table.
What happens if you have more than one table that needs to refer to an artist/artist's name? How do you re-use enum values across tables?
There are many other problems with this approach as well. I think that simplifying your database design like this does you a real disservice (foreign keys or having multiple tables are not a bad thing!).
I'm going to be honest - I stopped when I read...
I have used enumerations everywhere I
would normally use a foreign key to a
separate table--Artist name, Label
name, and several others.
If I understand correctly, that means there is an enumeration of all artists. But that enumeration of artists is definitely going to be a point of variation: there will be more artists. I sincerely doubt the record label never plans on increasing or changing the list of artists ;)
As such, in my opinion, that is an incorrect use of an enumeration.
I also don't think it's appropriate to perform an ALTER TABLE for what is inevitably a rather mundane use case. (Create/Read/Update/Destroy artist) I have no numbers to back up that opinion.
You have to look at it as a question of what information is an entity or an attribute of an entity: for a record label, artists are entities, but media types may not be. Artists have lots of information associated with them (name, genre, awards, web site url, seniority...) which suggests they are an entity, not an attribute of another entity such as Release. Also, Artists are Created/Read/Updated and Destroyed as part of regular everyday use of he system, further suggesting they are entities.
Entities tend to get their own table. Now, when you look at the Media Type of these Releases, you have to ask yourself whether Media Type has any other information... if it's anything more than Name you have a new Entity. For example, if your system has to keep track of whether a media type is obsolete, now there are 2 attributes for Media Type (name, is obsolete) and it should be a separate entity. If the Medai Types only have a Name within the scope of what you're building, then it's an attribute of another entity and should only be a column, not a table. At that point I would consider using an enumeration.
I dont think you can use enumerations in fields like artists. Its like you are restricting your application from growing. It will be really hard to maintain the column. Using ENUM is not a problem its own. But will be an issue in the following situations
When you need to add additional options to the enum colum. If you are table contains lots of data, it will take good time to rebuild your table when adding an additional option
When you need to port the the database to another technology (enum is not available in all database products, for eg MSSQL)