I've had a hard time trying to find good examples of how to manage database schemas and data between development, test, and production servers.
Here's our setup. Each developer has a virtual machine running our app and the MySQL database. It is their personal sandbox to do whatever they want. Currently, developers will make a change to the SQL schema and do a dump of the database to a text file that they commit into SVN.
We're wanting to deploy a continuous integration development server that will always be running the latest committed code. If we do that now, it will reload the database from SVN for each build.
We have a test (virtual) server that runs "release candidates." Deploying to the test server is currently a very manual process, and usually involves me loading the latest SQL from SVN and tweaking it. Also, the data on the test server is inconsistent. You end up with whatever test data the last developer to commit had on his sandbox server.
Where everything breaks down is the deployment to production. Since we can't overwrite the live data with test data, this involves manually re-creating all the schema changes. If there were a large number of schema changes or conversion scripts to manipulate the data, this can get really hairy.
If the problem was just the schema, It'd be an easier problem, but there is "base" data in the database that is updated during development as well, such as meta-data in security and permissions tables.
This is the biggest barrier I see in moving toward continuous integration and one-step-builds. How do you solve it?
A follow-up question: how do you track database versions so you know which scripts to run to upgrade a given database instance? Is a version table like Lance mentions below the standard procedure?
Thanks for the reference to Tarantino. I'm not in a .NET environment, but I found their DataBaseChangeMangement wiki page to be very helpful. Especially this Powerpoint Presentation (.ppt)
I'm going to write a Python script that checks the names of *.sql scripts in a given directory against a table in the database and runs the ones that aren't there in order based on a integer that forms the first part of the filename. If it is a pretty simple solution, as I suspect it will be, then I'll post it here.
I've got a working script for this. It handles initializing the DB if it doesn't exist and running upgrade scripts as necessary. There are also switches for wiping an existing database and importing test data from a file. It's about 200 lines, so I won't post it (though I might put it on pastebin if there's interest).
There are a couple of good options. I wouldn't use the "restore a backup" strategy.
Script all your schema changes, and have your CI server run those scripts on the database. Have a version table to keep track of the current database version, and only execute the scripts if they are for a newer version.
Use a migration solution. These solutions vary by language, but for .NET I use Migrator.NET. This allows you to version your database and move up and down between versions. Your schema is specified in C# code.
Your developers need to write change scripts (schema and data change) for each bug/feature they work on, not just simply dump the entire database into source control. These scripts will upgrade the current production database to the new version in development.
Your build process can restore a copy of the production database into an appropriate environment and run all the scripts from source control on it, which will update the database to the current version. We do this on a daily basis to make sure all the scripts run correctly.
Have a look at how Ruby on Rails does this.
First there are so called migration files, that basically transform database schema and data from version N to version N+1 (or in case of downgrading from version N+1 to N). Database has table which tells current version.
Test databases are always wiped clean before unit-tests and populated with fixed data from files.
The book Refactoring Databases: Evolutionary Database Design might give you some ideas on how to manage the database. A short version is readable also at http://martinfowler.com/articles/evodb.html
In one PHP+MySQL project I've had the database revision number stored in the database, and when the program connects to the database, it will first check the revision. If the program requires a different revision, it will open a page for upgrading the database. Each upgrade is specified in PHP code, which will change the database schema and migrate all existing data.
You could also look at using a tool like SQL Compare to script the difference between various versions of a database, allowing you to quickly migrate between versions
Name your databases as follows - dev_<<db>> , tst_<<db>> , stg_<<db>> , prd_<<db>> (Obviously you never should hardcode db names
Thus you would be able to deploy even the different type of db's on same physical server ( I do not recommend that , but you may have to ... if resources are tight )
Ensure you would be able to move data between those automatically
Separate the db creation scripts from the population = It should be always possible to recreate the db from scratch and populate it ( from the old db version or external data source
do not use hardcode connection strings in the code ( even not in the config files ) - use in the config files connection string templates , which you do populate dynamically , each reconfiguration of the application_layer which does need recompile is BAD
do use database versioning and db objects versioning - if you can afford it use ready products , if not develop something on your own
track each DDL change and save it into some history table ( example here )
DAILY backups ! Test how fast you would be able to restore something lost from a backup (use automathic restore scripts
even your DEV database and the PROD have exactly the same creation script you will have problems with the data, so allow developers to create the exact copy of prod and play with it ( I know I will receive minuses for this one , but change in the mindset and the business process will cost you much less when shit hits the fan - so force the coders to subscript legally whatever it makes , but ensure this one
This is something that I'm constantly unsatisfied with - our solution to this problem that is. For several years we maintained a separate change script for each release. This script would contain the deltas from the last production release. With each release of the application, the version number would increment, giving something like the following:
dbChanges_1.sql
dbChanges_2.sql
...
dbChanges_n.sql
This worked well enough until we started maintaining two lines of development: Trunk/Mainline for new development, and a maintenance branch for bug fixes, short term enhancements, etc. Inevitably, the need arose to make changes to the schema in the branch. At this point, we already had dbChanges_n+1.sql in the Trunk, so we ended up going with a scheme like the following:
dbChanges_n.1.sql
dbChanges_n.2.sql
...
dbChanges_n.3.sql
Again, this worked well enough, until we one day we looked up and saw 42 delta scripts in the mainline and 10 in the branch. ARGH!
These days we simply maintain one delta script and let SVN version it - i.e. we overwrite the script with each release. And we shy away from making schema changes in branches.
So, I'm not satisfied with this either. I really like the concept of migrations from Rails. I've become quite fascinated with LiquiBase. It supports the concept of incremental database refactorings. It's worth a look and I'll be looking at it in detail soon. Anybody have experience with it? I'd be very curious to hear about your results.
We have a very similar setup to the OP.
Developers develop in VM's with private DB's.
[Developers will soon be committing into private branches]
Testing is run on different machines ( actually in in VM's hosted on a server)
[Will soon be run by Hudson CI server]
Test by loading the reference dump into the db.
Apply the developers schema patches
then apply the developers data patches
Then run unit and system tests.
Production is deployed to customers as installers.
What we do:
We take a schema dump of our sandbox DB.
Then a sql data dump.
We diff that to the previous baseline.
that pair of deltas is to upgrade n-1 to n.
we configure the dumps and deltas.
So to install version N CLEAN we run the dump into an empty db.
To patch, apply the intervening patches.
( Juha mentioned Rail's idea of having a table recording the current DB version is a good one and should make installing updates less fraught. )
Deltas and dumps have to be reviewed before beta test.
I can't see any way around this as I've seen developers insert test accounts into the DB for themselves.
I'm afraid I'm in agreement with other posters. Developers need to script their changes.
In many cases a simple ALTER TABLE won't work, you need to modify existing data too - developers need to thing about what migrations are required and make sure they're scripted correctly (of course you need to test this carefully at some point in the release cycle).
Moreover, if you have any sense, you'll get your developers to script rollbacks for their changes as well so they can be reverted if need be. This should be tested as well, to ensure that their rollback not only executes without error, but leaves the DB in the same state as it was in previously (this is not always possible or desirable, but is a good rule most of the time).
How you hook that into a CI server, I don't know. Perhaps your CI server needs to have a known build snapshot on, which it reverts to each night and then applies all the changes since then. That's probably best, otherwise a broken migration script will break not just that night's build, but all subsequent ones.
Check out the dbdeploy, there are Java and .net tools already available, you could follow their standards for the SQL file layouts and schema version table and write your python version.
We are using command-line mysql-diff: it outputs a difference between two database schemas (from live DB or script) as ALTER script. mysql-diff is executed at application start, and if schema changed, it reports to developer. So developers do not need to write ALTERs manually, schema updates happen semi-automatically.
If you are in the .NET environment then the solution is Tarantino (archived). It handles all of this (including which sql scripts to install) in a NANT build.
I've written a tool which (by hooking into Open DBDiff) compares database schemas, and will suggest migration scripts to you. If you make a change that deletes or modifies data, it will throw an error, but provide a suggestion for the script (e.g. when a column in missing in the new schema, it will check if the column has been renamed and create xx - generated script.sql.suggestion containing a rename statement).
http://code.google.com/p/migrationscriptgenerator/ SQL Server only I'm afraid :( It's also pretty alpha, but it is VERY low friction (particularly if you combine it with Tarantino or http://code.google.com/p/simplescriptrunner/)
The way I use it is to have a SQL scripts project in your .sln. You also have a db_next database locally which you make your changes to (using Management Studio or NHibernate Schema Export or LinqToSql CreateDatabase or something). Then you execute migrationscriptgenerator with the _dev and _next DBs, which creates. the SQL update scripts for migrating across.
For oracle database we use oracle-ddl2svn tools.
This tool automated next process
for every db scheme get scheme ddls
put it under version contol
changes between instances resolved manually
Related
I've had a hard time trying to find good examples of how to manage database schemas and data between development, test, and production servers.
Here's our setup. Each developer has a virtual machine running our app and the MySQL database. It is their personal sandbox to do whatever they want. Currently, developers will make a change to the SQL schema and do a dump of the database to a text file that they commit into SVN.
We're wanting to deploy a continuous integration development server that will always be running the latest committed code. If we do that now, it will reload the database from SVN for each build.
We have a test (virtual) server that runs "release candidates." Deploying to the test server is currently a very manual process, and usually involves me loading the latest SQL from SVN and tweaking it. Also, the data on the test server is inconsistent. You end up with whatever test data the last developer to commit had on his sandbox server.
Where everything breaks down is the deployment to production. Since we can't overwrite the live data with test data, this involves manually re-creating all the schema changes. If there were a large number of schema changes or conversion scripts to manipulate the data, this can get really hairy.
If the problem was just the schema, It'd be an easier problem, but there is "base" data in the database that is updated during development as well, such as meta-data in security and permissions tables.
This is the biggest barrier I see in moving toward continuous integration and one-step-builds. How do you solve it?
A follow-up question: how do you track database versions so you know which scripts to run to upgrade a given database instance? Is a version table like Lance mentions below the standard procedure?
Thanks for the reference to Tarantino. I'm not in a .NET environment, but I found their DataBaseChangeMangement wiki page to be very helpful. Especially this Powerpoint Presentation (.ppt)
I'm going to write a Python script that checks the names of *.sql scripts in a given directory against a table in the database and runs the ones that aren't there in order based on a integer that forms the first part of the filename. If it is a pretty simple solution, as I suspect it will be, then I'll post it here.
I've got a working script for this. It handles initializing the DB if it doesn't exist and running upgrade scripts as necessary. There are also switches for wiping an existing database and importing test data from a file. It's about 200 lines, so I won't post it (though I might put it on pastebin if there's interest).
There are a couple of good options. I wouldn't use the "restore a backup" strategy.
Script all your schema changes, and have your CI server run those scripts on the database. Have a version table to keep track of the current database version, and only execute the scripts if they are for a newer version.
Use a migration solution. These solutions vary by language, but for .NET I use Migrator.NET. This allows you to version your database and move up and down between versions. Your schema is specified in C# code.
Your developers need to write change scripts (schema and data change) for each bug/feature they work on, not just simply dump the entire database into source control. These scripts will upgrade the current production database to the new version in development.
Your build process can restore a copy of the production database into an appropriate environment and run all the scripts from source control on it, which will update the database to the current version. We do this on a daily basis to make sure all the scripts run correctly.
Have a look at how Ruby on Rails does this.
First there are so called migration files, that basically transform database schema and data from version N to version N+1 (or in case of downgrading from version N+1 to N). Database has table which tells current version.
Test databases are always wiped clean before unit-tests and populated with fixed data from files.
The book Refactoring Databases: Evolutionary Database Design might give you some ideas on how to manage the database. A short version is readable also at http://martinfowler.com/articles/evodb.html
In one PHP+MySQL project I've had the database revision number stored in the database, and when the program connects to the database, it will first check the revision. If the program requires a different revision, it will open a page for upgrading the database. Each upgrade is specified in PHP code, which will change the database schema and migrate all existing data.
You could also look at using a tool like SQL Compare to script the difference between various versions of a database, allowing you to quickly migrate between versions
Name your databases as follows - dev_<<db>> , tst_<<db>> , stg_<<db>> , prd_<<db>> (Obviously you never should hardcode db names
Thus you would be able to deploy even the different type of db's on same physical server ( I do not recommend that , but you may have to ... if resources are tight )
Ensure you would be able to move data between those automatically
Separate the db creation scripts from the population = It should be always possible to recreate the db from scratch and populate it ( from the old db version or external data source
do not use hardcode connection strings in the code ( even not in the config files ) - use in the config files connection string templates , which you do populate dynamically , each reconfiguration of the application_layer which does need recompile is BAD
do use database versioning and db objects versioning - if you can afford it use ready products , if not develop something on your own
track each DDL change and save it into some history table ( example here )
DAILY backups ! Test how fast you would be able to restore something lost from a backup (use automathic restore scripts
even your DEV database and the PROD have exactly the same creation script you will have problems with the data, so allow developers to create the exact copy of prod and play with it ( I know I will receive minuses for this one , but change in the mindset and the business process will cost you much less when shit hits the fan - so force the coders to subscript legally whatever it makes , but ensure this one
This is something that I'm constantly unsatisfied with - our solution to this problem that is. For several years we maintained a separate change script for each release. This script would contain the deltas from the last production release. With each release of the application, the version number would increment, giving something like the following:
dbChanges_1.sql
dbChanges_2.sql
...
dbChanges_n.sql
This worked well enough until we started maintaining two lines of development: Trunk/Mainline for new development, and a maintenance branch for bug fixes, short term enhancements, etc. Inevitably, the need arose to make changes to the schema in the branch. At this point, we already had dbChanges_n+1.sql in the Trunk, so we ended up going with a scheme like the following:
dbChanges_n.1.sql
dbChanges_n.2.sql
...
dbChanges_n.3.sql
Again, this worked well enough, until we one day we looked up and saw 42 delta scripts in the mainline and 10 in the branch. ARGH!
These days we simply maintain one delta script and let SVN version it - i.e. we overwrite the script with each release. And we shy away from making schema changes in branches.
So, I'm not satisfied with this either. I really like the concept of migrations from Rails. I've become quite fascinated with LiquiBase. It supports the concept of incremental database refactorings. It's worth a look and I'll be looking at it in detail soon. Anybody have experience with it? I'd be very curious to hear about your results.
We have a very similar setup to the OP.
Developers develop in VM's with private DB's.
[Developers will soon be committing into private branches]
Testing is run on different machines ( actually in in VM's hosted on a server)
[Will soon be run by Hudson CI server]
Test by loading the reference dump into the db.
Apply the developers schema patches
then apply the developers data patches
Then run unit and system tests.
Production is deployed to customers as installers.
What we do:
We take a schema dump of our sandbox DB.
Then a sql data dump.
We diff that to the previous baseline.
that pair of deltas is to upgrade n-1 to n.
we configure the dumps and deltas.
So to install version N CLEAN we run the dump into an empty db.
To patch, apply the intervening patches.
( Juha mentioned Rail's idea of having a table recording the current DB version is a good one and should make installing updates less fraught. )
Deltas and dumps have to be reviewed before beta test.
I can't see any way around this as I've seen developers insert test accounts into the DB for themselves.
I'm afraid I'm in agreement with other posters. Developers need to script their changes.
In many cases a simple ALTER TABLE won't work, you need to modify existing data too - developers need to thing about what migrations are required and make sure they're scripted correctly (of course you need to test this carefully at some point in the release cycle).
Moreover, if you have any sense, you'll get your developers to script rollbacks for their changes as well so they can be reverted if need be. This should be tested as well, to ensure that their rollback not only executes without error, but leaves the DB in the same state as it was in previously (this is not always possible or desirable, but is a good rule most of the time).
How you hook that into a CI server, I don't know. Perhaps your CI server needs to have a known build snapshot on, which it reverts to each night and then applies all the changes since then. That's probably best, otherwise a broken migration script will break not just that night's build, but all subsequent ones.
Check out the dbdeploy, there are Java and .net tools already available, you could follow their standards for the SQL file layouts and schema version table and write your python version.
We are using command-line mysql-diff: it outputs a difference between two database schemas (from live DB or script) as ALTER script. mysql-diff is executed at application start, and if schema changed, it reports to developer. So developers do not need to write ALTERs manually, schema updates happen semi-automatically.
If you are in the .NET environment then the solution is Tarantino (archived). It handles all of this (including which sql scripts to install) in a NANT build.
I've written a tool which (by hooking into Open DBDiff) compares database schemas, and will suggest migration scripts to you. If you make a change that deletes or modifies data, it will throw an error, but provide a suggestion for the script (e.g. when a column in missing in the new schema, it will check if the column has been renamed and create xx - generated script.sql.suggestion containing a rename statement).
http://code.google.com/p/migrationscriptgenerator/ SQL Server only I'm afraid :( It's also pretty alpha, but it is VERY low friction (particularly if you combine it with Tarantino or http://code.google.com/p/simplescriptrunner/)
The way I use it is to have a SQL scripts project in your .sln. You also have a db_next database locally which you make your changes to (using Management Studio or NHibernate Schema Export or LinqToSql CreateDatabase or something). Then you execute migrationscriptgenerator with the _dev and _next DBs, which creates. the SQL update scripts for migrating across.
For oracle database we use oracle-ddl2svn tools.
This tool automated next process
for every db scheme get scheme ddls
put it under version contol
changes between instances resolved manually
I am working on a Yii framework based app where I have to test the app on my local machine and then when ready move the changes to the production server.
the app will be developed as people are using it and ask for new features. So when I make changes to my DB schema on the test machine I have to apply these to the schema of the production DB without destroying data there.
is there a recommended and convenient way to deal with this? syncing source code is less of an issue, i am using svn and can do svn export ; rsync ...
MySQLWorkbench can be helpful for syncing db schema as well as other database design tasks.
Yii does support Migrations (since v1.1.6), although it can be more trouble than it's worth depending on how often you make changes and how collaborative your project is.
Another approach I've used is to keep a log of update statements in svn and basically handled the migrations manually.
The best approach is going to depend on the cost/benefits to your particular project/workflow.
You can try SQLyog's Schema Synchronization Tool, which is a visual comparison/synchronization tool designed for developers who work between different MySQL servers or need to keep databases between two MySQL servers in sync. This means reporting the differences between tables, indexes, columns and routines of two databases, and generating scripts to bring them in Sync. Only the Schema will be synced in the target.
For a similar project we
use MySQLWorkbench (MWB) to design and edit the schema
share the .mwb file through a VCS.
When one of us is comfortable with a change he uses mysqldump --complete-insert... on the production and test schemas to generate a copy of the existing test and production data with field names
pull out all the production server insert statements in (3) and put them in protected/data/insert.sql
use the "forward engineer" menu item in MWB on the modified model to generate sql to save to a file called protected/data/create.sql, hand-editing as appropriate (be sure to use the if exists clause to reduce errors)
write a drop.sql file based on drop statements in (3)
use MWB, run the sql (drop.sql, create.sql, insert.sql) after issuing the appropriate "use database" command that identifies the production database
deal with all the errors in (7) by getting rid of any invalid inserts due to columns/fields that are not needed in the new models/schema. Rerun (7)
deal with new fields in (7) that need data other than Null. Rerun (7)
Now you have a snapshot of your schema (drop.sql create.sql) and your data that should revive either your test or production server if you ever have a problem. And you have a "fixture" of the data that was in your production server (insert.sql) that can be used to bring your test server up to speed, or as a backup of the production server data (that will quickly be outdated). Obviously all the foreign key relationships are what are really painful, so it's rare that the insert.sql is useful for anything except upgrading the schema and restoring the production data after this change. Clearly it takes some time to work out the kinks in the process so that the delay between (3) and (9) is small enough that the production server users don't notice the downtime.
Clearly "Rerun (7)" gets repetitive and quickly turns into a shell script that calls mysql directly. Also other steps in the sql editing process become sed scripts.
Have a look at schema comparison tool in dbForge Studio for MySQL.
This tool will help you to compare and synchronize two databases or a database project with specified database.
Also there is separate tool - dbForge Schema Compare for MySQL.
I need ability to compare two similar databases. One will be slightly newer than the other and have changes to the structure of the database as well as possibly the content within it.
So far I have tried using liquibase but it doesn't seem to be comparing properly.
I have also tried the MySQL Diff Perl module which works but doesn't consider content.
Main Question:
Does anyone know any solutions that will give back SQL for both structural and content differences and generate a SQL script?
A bit more info:
The intended use for this is when making updates and installing MODs to phpBB so that the forum can be included in the build process along with the rest of our website. Which has a 4 tier process (local, development, staging, production).
When installing the phpBB updates and MODs I will make a dump of the current production database and lock the site so no new data can be added whilst I make changes. That way databases shouldn't come out of sync.
When installing MODs and updates sometimes the database structure changes and also the data within tables, especially when adding things requiring extra permissions etc.
The solution I use therefore will be used to compare the local database with the upgraded changes to the production database, providing me with a script I can run on each tier in the build process, rather than manually installing the update/MOD on each.
You can use SQLyog Database synchronization tool to sync two databases,either one-way or two-way. By far this is the best data comparison tool for MySQL GUI. And, Schema sync for schema comparisons between two databases.
Both tools can generate SQL scripts.
I've actually found a way to do it via Navicat for MySQL using the Tools > Structure Syncronization option.
This will give SQL statements for differences in structure between the two databases.
Then do do the data differences you can use Data Syncornization.
I've managed to copy out the SQL script for differences in structure. However the data syncronization seems to be more of an internal Navicat thing. I'm sure there's a way that the queries could be extracted though.
Please note I'm using a license version so not sure if its available in the free to use one.
Wondering if it is possible to have a version control of a MySQL database.
I realize this question has been asked before however the newest is almost a year ago, and at the rate things change...
The problem is coming that each developer has apache/MySQL/PHP on their own computers to which they sometimes edit the database. Its rather inconvenient if they have to send an email to all the other developers and then manually edit the test servers database.
How do you deal with this problem?
Thanks
This is not a MySQL-related solution in itself, but we've had a lot of success with a product called liquibase. (http://www.liquibase.org/)
It's a migration solution which covers many different database vendors, allowing all database changes to be coded in configuration files, all of which are kept in Subversion. Since all configuration is kept in XML files, it's easy to merge other people's changes into the mainline script and it plays well with tags and branches.
The database can be brought up to the current revision level by running the "update database" command. Most changes also have the ability to roll-back a database change, which can be helpful too. I would recommend following the practice of making sure you get current before running the migration, as this would likely be easiest.
Finally, when it comes to a production delivery, you can choose to have all the database changes output as a full SQL script so it can allow DBAs to run it and maintain a separation of duties.
So far, it's worked like a charm.
Well we use Rails which keeps all the change in the migration files. I know that a couple of PHP frameworks do the same thing - Symphony for instance. So when all the changes are merged in our repository ( we user mercurial) - we can see all the changes in migrations that need to or were applied on database in development. Than the person responsible for production rolls out code to production after a full backup is made. However if you don't use a PHP framework that takes care of this than, awied's suggestion sounds very interesting - I haven't heard of liquidbase before but I will definitely check it out.
There is a tool called iBatis, now called MyBatis that handles versions of databases perfectly.
It takes a little work to have all your changes in script instead of with a graphical tool, but, if you are familiar with coding, it's not a problem.
When you have multiple databases (like dev-test-prod), you just make 3 environment files and you can update one environment with only one command-line instruction.
What is the simplest way of keeping track of changes to a projects database structure?
When I change something about the database (eg, add a new table, add a new field to an existing table, add an index etc), I want that to be propagated to the rest of the team, and ultimately the production server, with the minimal fuss and effort.
At the moment, the solution is pretty weak and relies of people remembering to do things, which is an accident waiting to happen.
Everything else is managed with standard revision control software (Perforce in our case).
We use MySQL, so tools that understand that would be helpful, though I would also be interested to learn how other places are handling this anyway, regardless of database engine.
You can dump the schema and commit it -- and the RCS will take care of the changes between versions.
You can get a tool like Sql Compare from Red-Gate which allows you to point to two databases and it will let you know what is different, and will build alter scripts for you.
If you're using .NET(Visual Studio), you can create a Database project and check that into source control.
This has alrady been discussed a lot I think. Anyhow I really like Rails approach to the issue. It's code that has three things:
The version number
The way of applying the changes (updates a version table)
The way of rolling the changes back (sets the version on the version table to the previous)
So, each time you make a changeset you create this code file that can rollback or upgrade the database schema when you execute it.
This, being code, you can commit in any revision control system. You commit the first dump and then the scripts only.
The great thing about this approach is that you can easily distribute the database changes to customers, whereas with a standard just dump the schema and update it approach generating an upgrade/rollback script is a nuisance
In my company each developer is encouraged to save all db sctructure changes to a script files in the folder containing module's revision number. These scripts are kept in svn repository.
When application starts, the db upgrade code compares current db version and code version and if the code is newer - looks into scripts folder and applies all db changes automatically.
This way every instance of application (on production or developers machines) always upgrades db to their code version and it works great.
Of course, some automation could be added - if we find a suitable tool.
Poor mans version control:
Separate file for each object (table, view, etc)
When altering tables, you want to diff CREATE TABLE to CREATE TABLE. Source code history is for communicating a story. You can't do a meaningful diff of CREATE TABLE and ALTER TABLE
Try to make changes to the files, then commit them to source control, then commit them to the SQL database. Most tools poorly support this because you shouldn't commit to source control until you test and you can't test without putting the code into SQL. So in practice, you try to use SQL Redgate to compare your files to the SQL database. Failing that, you adopt a harsh policy of dropping everything in the database and replacing it with what made it into source control.
Change scripts usually are single use, but applications exist, like wordpress, where you need to move the schema from 1.0 to 1.1, 1.1 to 1.5, etc. Each of those should be under source control and modified as such (i.e. as you find bugs in the script that moves you from 1.0 to 1.1, you create a new version of that script, not yet-another script)