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== Introduction == Have you seen this situation before?* Your team is writing an enterprise application around a database * Since everyone is building around the same database, the schema of the database is in flux * Everyone has their own "local" copies of the database * Every time someone changes the schema, all of these copies need the latest schema to work with the latest build of the code * Every time you deploy to to a staging or production database, the schema needs to work with the latest build of the code * Factors such as schema dependencies, data changes, configuration changes and remote developers muddy the water How do you currently address this problem of keeping the database versions in working order?You may choose to implement these changes using data cleansing utilities, often the heart of extract-transform-load (ETL) tools, examples of which are listed in Table 1.You may choose to implement each logical script as a collection of physical scripts, perhaps one for each development iteration or even one for each individual database refactoring, or you may choose to implement as a single script that includes the ability to run only a portion of the changes.Now all database development is done “off line” and in a “sandbox” environment (this should make your dba stand up and sing! All user defined functions and stored procedures can be fully unit tested using representative test data automatically generated by the toolset.And best of all, this new Visual Studio sku fully integrates into Team Foundation Server so your database schema (SQL scripts) can be put under source control just like any other C#, Biz Talk or Web Application!
This log contains the data definition language (DDL) source code that implements all database schema changes in the order that they were applied throughout the course of a project.This includes structural changes such as adding, dropping, renaming, or modifying things such as tables, views, columns, and indices. This log contains the source code for future changes to the database schema that are to be run after the deprecation period for database changes.[ The Process of Database Refactoring] argues that changing your database schema is inherently more difficult than changing application source code – other developers on your project team need time to update their own code and worse yet other applications may access your database and therefore need to be modified and deployed as well.Less integrated ones get consistent migration strategy only at individual product level, and the tools are usually ad-hoc.For example, Ruby on Rails has a very refreshing idea of [ Record/Active Migrations].