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At the other end of the scale is a data model designed for extreme extensibility. If you ever hear anyone bragging that their data model is entirely metadata d

• feoren 5y ago
  Secret hacker pro-tip: inner platforms and key/value pair representations do not actually improve extensibility. You always have a schema -- you get to decide whether it's explicit or implicit. Their problem isn't that their data model is too extensible: it's that it's plain old bad.
• jiggawatts 5y ago
  One underlying reason for this is that DBMS systems have an unnecessary source of complexity: They have a separate Data Manipulation Language (DML) and a Data Description Language (DDL). They really ought to be unified, but few (any?) mainstream SQL databases are homoiconic in this way. E.g.: It should be possible to take a query definition, request its columns ("schema only" execution), and then insert or merge the columns into a table definition somewhere. Something like: SELECT SCHEMA( SELECT * FROM "blah" ) INTO "tablename" When a black market is formed, it's a sign that there is an unmet demand. When you see the exact same "wrong" design pattern turn up over and over, it's a sign that the underlying system isn't meeting the needs of the developers.
  • cerved 5y ago
    it sounds like you're making an interesting point but I'm afraid I don't follow, could you elaborate?
    • jiggawatts 5y ago
      The "bad" design that keeps cropping up over and over is the second system effect: Tables, relationships, and columns defined as data in a few simple tables, instead of being defined explicitly in the SQL schema as expected. This is less than optimal for lots of reasons: duplication of metadata, inefficient query plans, no foreign keys, inability to use most kinds of indexes effectively, etc... However, the need is real: the ability to easily extend or generate table schemas without having to switch languages. You can argue that this is "not that hard", but you'd be absolutely wrong. It's obscenely difficult. I've tried, failed, and have given up. One use-case I had was automatically generating tables for importing data from PowerShell. My goal was to be able to write something like this: Get-Process | Export-Sql -ConnectionString '...' -TableName 'Processes' And have the "Export-Sql" command automatically generate the table schema on the fly based on the input columns it sees. I even wanted to be able to represent object hierarchies as sets of related tables with parent-child foreign key relationships automatically put in. I got a proof-of-concept working, but there were just too many edge-cases. Things like maximum lengths for key or index columns, maximum row size, inability to switch column types on the fly, etc... So what to do other people do? They also give up and resort to defining a single table that has the columns: "TableName, RowId, ColumnName, ColumnValue" and call it a day. I mean... what other options are there? Bang your head against the wall for months trying to deal with idiotic things like identifier length limits? Correctly escaping arbitrary input strings? Generating hundreds of distinct commands that cannot be parametrised and hope you don't have a SQL injection vulnerability lurking in there somewhere? It's nuts! Have you seen just how much code it takes to take an arbitrary table, one with dozens of foreign key references, several filtered multi-column indexes, and views that depend on it, and then insert a column in a specific position? You have to drop everything, copy the table, rename, and then recreate everything. Doing this in code would be... I dunno... a few hundred thousand lines? That's absurd. You're not doing it. I'm not doing it. Microsoft did it once for SQL Server Management Studio, and I bet they're not rewriting that code in a hurry! But go back to the "bad" schema example before: Is it really that bad? What if the database engine had the ability to store common prefixes just once, instead of repeating them for each row? What if the schema looked like this: Database, Owner, Table, Column, Value Starting to look familiar? A bit like [server].[database].[dbo].[Table] perhaps, familiar to every user of Microsoft SQL Server? There's a natural hierarchy for describing the data, that lends itself well to being represented as a B-Tree, along with the data itself! That's what the "bad" schema is doing: it's representing the data with the most natural representation! It's not wrong at all! The problem is that database engines have all sorts of features and optimisations that we want that isn't directly compatible with the naive implementation of the bad schema. Constraints, foreign keys, efficient storage, indexing, etc... However, none of these features are fundamentally incompatible with an API that merely "pretends" that the data is stored in a single flat list that can have its schema updated with a simple insert. The database engine could simply factor out the schema part and the data part into different physical storage layouts, with all the usual efficiencies such as not having to repeat column names for every row. To summarise: we could have our cake and eat it too. Database engines could be developed that use ordinary select/insert/delete/update statements to modify the schema, and have it perform just as efficiently as a database that uses clumsy statements like "alter table add column". In this world, a database schema upgrade could be as simple as a single literal "MERGE" statement!