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    <p>I'm maintaining a 10 year old system that has a central EAV model with 10M+ entities, 500M+ values and hundreds of attributes. Some design considerations from my experience:</p> <p>If you have any business logic that applies to a specific attribute it's worth having that attribute as an explicit column. The EAV attributes should really be stuff that is generic, the application shouldn't distinguish attribute A from attribute B. If you find a literal reference to an EAV attribute in the code, odds are that it should be an explicit column.</p> <p>Having significant amounts of empty columns isn't a big technical issue. It does need good coding and documentation practices to compartmentalize different concerns that end up in one table:</p> <ul> <li>Have conventions and rules that let you know which part of your application reads and modifies which part of the data.</li> <li>Use views to ease poking around the database with debugging tools.</li> <li>Create and maintain test data generators so you can easily create schema conforming dummy data for the parts of the model that you are not currently interested in.</li> <li>Use rigorous database versioning. The only way to make schema changes should be via a tool that keeps track of and applies change scripts. Postgresql has transactional DDL, that is one killer feature for automating schema changes.</li> </ul> <p>Postgresql doesn't really like skinny tables. Each attribute value results in 32 bytes of data storage overhead in addition to the extra work of traversing all the rows to pull the data together. If you mostly read and write the attributes as a batch, consider serializing the data into the row in some way. <code>attr_ids int[], attr_values text[]</code> is one option, hstore is another, or something client side, like json or protobuf, if you don't need to touch anything specific on the database side.</p> <p>Don't go out of your way to put everything into one single entity table. If they don't share any attributes in a sensible way, use multiple instantitions of the specific EAV pattern you use. But do try to use the same pattern and share any accessor code between the different instatiations. You can always parametrise the code on the entity name.</p> <p>Always keep in mind that code is data and data is code. You need to find the correct balance between pushing decisions into the meta-model and expressing them as code. If you make the meta-model do too much, modifying it will need the same kind of ability to understand the system, versioning tools, QA procedures, staging as your code, but it will have none of the tools. In essence you will be doing programming in a very awkward non-standard language. On the other hand, if you leave too much in the code, every trivial change will need a new version of your software. People tend to err on the side of making the meta-model too complex. Building developer tools for meta-models is hard and tedious work and has limited benefit. On the other hand, making the release process cheaper by automating everything that happens from commit to deploy has many side benefits. </p>
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    1. POis EAV - Hybrid a bad database design choice
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    1. COThanks for your reply, we are trying to use a hybrid eav model where each entity has it own tables and attributes but only commonly used properties are kept in "properties" table, you can think of it as tags so we would be able to create or attach any number of tags to any given entity.
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    2. COInstead of using columns for certain logic, how about creating two kind of attributes, simple and hard ones. Where hard properties can have business logic in code?
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