I'm doing a web app, and I need to make a branch for some major changes, the thing is, these changes require changes to the database schema, so I'd like to put the entire database under git as well.
How do I do that? is there a specific folder that I can keep under a git repository? How do I know which one? How can I be sure that I'm putting the right folder?
I need to be sure, because these changes are not backward compatible; I can't afford to screw up.
The database in my case is PostgreSQL
Edit:
Someone suggested taking backups and putting the backup file under version control instead of the database. To be honest, I find that really hard to swallow.
There has to be a better way.
Update:
OK, so there' no better way, but I'm still not quite convinced, so I will change the question a bit:
I'd like to put the entire database under version control, what database engine can I use so that I can put the actual database under version control instead of its dump?
Would sqlite be git-friendly?
Since this is only the development environment, I can choose whatever database I want.
Edit2:
What I really want is not to track my development history, but to be able to switch from my "new radical changes" branch to the "current stable branch" and be able for instance to fix some bugs/issues, etc, with the current stable branch. Such that when I switch branches, the database auto-magically becomes compatible with the branch I'm currently on.
I don't really care much about the actual data.
Take a database dump, and version control that instead. This way it is a flat text file.
Personally I suggest that you keep both a data dump, and a schema dump. This way using diff it becomes fairly easy to see what changed in the schema from revision to revision.
If you are making big changes, you should have a secondary database that you make the new schema changes to and not touch the old one since as you said you are making a branch.
I'm starting to think of a really simple solution, don't know why I didn't think of it before!!
Duplicate the database, (both the schema and the data).
In the branch for the new-major-changes, simply change the project configuration to use the new duplicate database.
This way I can switch branches without worrying about database schema changes.
EDIT:
By duplicate, I mean create another database with a different name (like my_db_2); not doing a dump or anything like that.
Use something like LiquiBase this lets you keep revision control of your Liquibase files. you can tag changes for production only, and have lb keep your DB up to date for either production or development, (or whatever scheme you want).
Irmin (branching + time travel)
Flur.ee (immutable + time travel + graph query)
XTDB (formerly called 'CruxDB') (time travel + query)
TerminusDB (immutable + branching + time travel + Graph Query!)
DoltDB (branching + time-travel + SQL query)
Quadrable (branching + remote state verification)
EdgeDB (no real time travel, but migrations derived by the compiler after schema changes)
Migra (diffing for Postgres schemas/data. Auto-generate migration scripts, auto-sync db state)
ImmuDB (immutable + time-travel)
I've come across this question, as I've got a similar problem, where something approximating a DB based Directory structure, stores 'files', and I need git to manage it. It's distributed, across a cloud, using replication, hence it's access point will be via MySQL.
The gist of the above answers, seem to similarly suggest an alternative solution to the problem asked, which kind of misses the point, of using Git to manage something in a Database, so I'll attempt to answer that question.
Git is a system, which in essence stores a database of deltas (differences), which can be reassembled, in order, to reproduce a context. The normal usage of git assumes that context is a filesystem, and those deltas are diff's in that file system, but really all git is, is a hierarchical database of deltas (hierarchical, because in most cases each delta is a commit with at least 1 parents, arranged in a tree).
As long as you can generate a delta, in theory, git can store it. The problem is normally git expects the context, on which it's generating delta's to be a file system, and similarly, when you checkout a point in the git hierarchy, it expects to generate a filesystem.
If you want to manage change, in a database, you have 2 discrete problems, and I would address them separately (if I were you). The first is schema, the second is data (although in your question, you state data isn't something you're concerned about). A problem I had in the past, was a Dev and Prod database, where Dev could take incremental changes to the schema, and those changes had to be documented in CVS, and propogated to live, along with additions to one of several 'static' tables. We did that by having a 3rd database, called Cruise, which contained only the static data. At any point the schema from Dev and Cruise could be compared, and we had a script to take the diff of those 2 files and produce an SQL file containing ALTER statements, to apply it. Similarly any new data, could be distilled to an SQL file containing INSERT commands. As long as fields and tables are only added, and never deleted, the process could automate generating the SQL statements to apply the delta.
The mechanism by which git generates deltas is diff and the mechanism by which it combines 1 or more deltas with a file, is called merge. If you can come up with a method for diffing and merging from a different context, git should work, but as has been discussed you may prefer a tool that does that for you. My first thought towards solving that is this https://git-scm.com/book/en/v2/Customizing-Git-Git-Configuration#External-Merge-and-Diff-Tools which details how to replace git's internal diff and merge tool. I'll update this answer, as I come up with a better solution to the problem, but in my case I expect to only have to manage data changes, in-so-far-as a DB based filestore may change, so my solution may not be exactly what you need.
There is a great project called Migrations under Doctrine that built just for this purpose.
Its still in alpha state and built for php.
http://docs.doctrine-project.org/projects/doctrine-migrations/en/latest/index.html
Take a look at RedGate SQL Source Control.
http://www.red-gate.com/products/sql-development/sql-source-control/
This tool is a SQL Server Management Studio snap-in which will allow you to place your database under Source Control with Git.
It's a bit pricey at $495 per user, but there is a 28 day free trial available.
NOTE
I am not affiliated with RedGate in any way whatsoever.
I've released a tool for sqlite that does what you're asking for. It uses a custom diff driver leveraging the sqlite projects tool 'sqldiff', UUIDs as primary keys, and leaves off the sqlite rowid. It is still in alpha so feedback is appreciated.
Postgres and mysql are trickier, as the binary data is kept in multiple files and may not even be valid if you were able to snapshot it.
https://github.com/cannadayr/git-sqlite
I want to make something similar, add my database changes to my version control system.
I am going to follow the ideas in this post from Vladimir Khorikov "Database versioning best practices". In summary i will
store both its schema and the reference data in a source control system.
for every modification we will create a separate SQL script with the changes
In case it helps!
You can't do it without atomicity, and you can't get atomicity without either using pg_dump or a snapshotting filesystem.
My postgres instance is on zfs, which I snapshot occasionally. It's approximately instant and consistent.
I think X-Istence is on the right track, but there are a few more improvements you can make to this strategy. First, use:
$pg_dump --schema ...
to dump the tables, sequences, etc and place this file under version control. You'll use this to separate the compatibility changes between your branches.
Next, perform a data dump for the set of tables that contain configuration required for your application to operate (should probably skip user data, etc), like form defaults and other data non-user modifiable data. You can do this selectively by using:
$pg_dump --table=.. <or> --exclude-table=..
This is a good idea because the repo can get really clunky when your database gets to 100Mb+ when doing a full data dump. A better idea is to back up a more minimal set of data that you require to test your app. If your default data is very large though, this may still cause problems though.
If you absolutely need to place full backups in the repo, consider doing it in a branch outside of your source tree. An external backup system with some reference to the matching svn rev is likely best for this though.
Also, I suggest using text format dumps over binary for revision purposes (for the schema at least) since these are easier to diff. You can always compress these to save space prior to checking in.
Finally, have a look at the postgres backup documentation if you haven't already. The way you're commenting on backing up 'the database' rather than a dump makes me wonder if you're thinking of file system based backups (see section 23.2 for caveats).
What you want, in spirit, is perhaps something like Post Facto, which stores versions of a database in a database. Check this presentation.
The project apparently never really went anywhere, so it probably won't help you immediately, but it's an interesting concept. I fear that doing this properly would be very difficult, because even version 1 would have to get all the details right in order to have people trust their work to it.
This question is pretty much answered but I would like to complement X-Istence's and Dana the Sane's answer with a small suggestion.
If you need revision control with some degree of granularity, say daily, you could couple the text dump of both the tables and the schema with a tool like rdiff-backup which does incremental backups. The advantage is that instead of storing snapshots of daily backups, you simply store the differences from the previous day.
With this you have both the advantage of revision control and you don't waste too much space.
In any case, using git directly on big flat files which change very frequently is not a good solution. If your database becomes too big, git will start to have some problems managing the files.
Here is what i am trying to do in my projects:
separate data and schema and default data.
The database configuration is stored in configuration file that is not under version control (.gitignore)
The database defaults (for setting up new Projects) is a simple SQL file under version control.
For the database schema create a database schema dump under the version control.
The most common way is to have update scripts that contains SQL Statements, (ALTER Table.. or UPDATE). You also need to have a place in your database where you save the current version of you schema)
Take a look at other big open source database projects (piwik,or your favorite cms system), they all use updatescripts (1.sql,2.sql,3.sh,4.php.5.sql)
But this a very time intensive job, you have to create, and test the updatescripts and you need to run a common updatescript that compares the version and run all necessary update scripts.
So theoretically (and thats what i am looking for) you could
dumped the the database schema after each change (manually, conjob, git hooks (maybe before commit))
(and only in some very special cases create updatescripts)
After that in your common updatescript (run the normal updatescripts, for the special cases) and then compare the schemas (the dump and current database) and then automatically generate the nessesary ALTER Statements. There some tools that can do this already, but haven't found yet a good one.
What I do in my personal projects is, I store my whole database to dropbox and then point MAMP, WAMP workflow to use it right from there.. That way database is always up-to-date where ever I need to do some developing. But that's just for dev! Live sites is using own server for that off course! :)
Storing each level of database changes under git versioning control is like pushing your entire database with each commit and restoring your entire database with each pull.
If your database is so prone to crucial changes and you cannot afford to loose them, you can just update your pre_commit and post_merge hooks.
I did the same with one of my projects and you can find the directions here.
That's how I do it:
Since your have free choise about DB type use a filebased DB like e.g. firebird.
Create a template DB which has the schema that fits your actual branch and store it in your repository.
When executing your application programmatically create a copy of your template DB, store it somewhere else and just work with that copy.
This way you can put your DB schema under version control without the data. And if you change your schema you just have to change the template DB
We used to run a social website, on a standard LAMP configuration. We had a Live server, Test server, and Development server, as well as the local developers machines. All were managed using GIT.
On each machine, we had the PHP files, but also the MySQL service, and a folder with Images that users would upload. The Live server grew to have some 100K (!) recurrent users, the dump was about 2GB (!), the Image folder was some 50GB (!). By the time that I left, our server was reaching the limit of its CPU, Ram, and most of all, the concurrent net connection limits (We even compiled our own version of network card driver to max out the server 'lol'). We could not (nor should you assume with your website) put 2GB of data and 50GB of images in GIT.
To manage all this under GIT easily, we would ignore the binary folders (the folders containing the Images) by inserting these folder paths into .gitignore. We also had a folder called SQL outside the Apache documentroot path. In that SQL folder, we would put our SQL files from the developers in incremental numberings (001.florianm.sql, 001.johns.sql, 002.florianm.sql, etc). These SQL files were managed by GIT as well. The first sql file would indeed contain a large set of DB schema. We don't add user-data in GIT (eg the records of the users table, or the comments table), but data like configs or topology or other site specific data, was maintained in the sql files (and hence by GIT). Mostly its the developers (who know the code best) that determine what and what is not maintained by GIT with regards to SQL schema and data.
When it got to a release, the administrator logs in onto the dev server, merges the live branch with all developers and needed branches on the dev machine to an update branch, and pushed it to the test server. On the test server, he checks if the updating process for the Live server is still valid, and in quick succession, points all traffic in Apache to a placeholder site, creates a DB dump, points the working directory from 'live' to 'update', executes all new sql files into mysql, and repoints the traffic back to the correct site. When all stakeholders agreed after reviewing the test server, the Administrator did the same thing from Test server to Live server. Afterwards, he merges the live branch on the production server, to the master branch accross all servers, and rebased all live branches. The developers were responsible themselves to rebase their branches, but they generally know what they are doing.
If there were problems on the test server, eg. the merges had too many conflicts, then the code was reverted (pointing the working branch back to 'live') and the sql files were never executed. The moment that the sql files were executed, this was considered as a non-reversible action at the time. If the SQL files were not working properly, then the DB was restored using the Dump (and the developers told off, for providing ill-tested SQL files).
Today, we maintain both a sql-up and sql-down folder, with equivalent filenames, where the developers have to test that both the upgrading sql files, can be equally downgraded. This could ultimately be executed with a bash script, but its a good idea if human eyes kept monitoring the upgrade process.
It's not great, but its manageable. Hope this gives an insight into a real-life, practical, relatively high-availability site. Be it a bit outdated, but still followed.
Update Aug 26, 2019:
Netlify CMS is doing it with GitHub, an example implementation can be found here with all information on how they implemented it netlify-cms-backend-github
I say don't. Data can change at any given time. Instead you should only commit data models in your code, schema and table definitions (create database and create table statements) and sample data for unit tests. This is kinda the way that Laravel does it, committing database migrations and seeds.
I would recommend neXtep (Link removed - Domain was taken over by a NSFW-Website) for version controlling the database it has got a good set of documentation and forums that explains how to install and the errors encountered. I have tested it for postgreSQL 9.1 and 9.3, i was able to get it working for 9.1 but for 9.3 it doesn't seems to work.
Use a tool like iBatis Migrations (manual, short tutorial video) which allows you to version control the changes you make to a database throughout the lifecycle of a project, rather than the database itself.
This allows you to selectively apply individual changes to different environments, keep a changelog of which changes are in which environments, create scripts to apply changes A through N, rollback changes, etc.
I'd like to put the entire database under version control, what
database engine can I use so that I can put the actual database under
version control instead of its dump?
This is not database engine dependent. By Microsoft SQL Server there are lots of version controlling programs. I don't think that problem can be solved with git, you have to use a pgsql specific schema version control system. I don't know whether such a thing exists or not...
Use a version-controlled database, of which there are now several.
https://www.dolthub.com/blog/2021-09-17-database-version-control/
These products don't apply version control on top of another type of database -- they are their own database engines that support version control operations. So you need to migrate to them or start building on them in the first place.
I write one of them, DoltDB, which combines the interfaces of MySQL and Git. Check it out here:
https://github.com/dolthub/dolt
I wish it were simpler. Checking in the schema as a text file is a good start to capture the structure of the DB. For the content, however, I have not found a cleaner, better method for git than CSV files. One per table. The DB can then be edited on multiple branches and merges extremely well.
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I am part of a development team currently working with a database that does not have any kind of source control. We work with SQL Server 2008 R2 and have always managed the DB directly with SSMS. It now has ~340 tables and ~1600 stored procedures, plus a few triggers and views, so it is not a small DB.
My goal is to have the DB under version control, so I have been reading articles, like Scott Allen's series and many old SO related questions. But I am still unable to decide on how to proceed.
What I'm thinking of is to script the database schema in one file, then procedures, triggers and views in one file each. Then keep everything versioned under Mercurial. But of course, every member of the team can access SSMS and directly change the schema and procedures, with the possibility that any of us can forget to replicate those changes in the versioned files.
What better options are there? And, did I forget any element worth having source control of? My biggest concern is that most of the literature I found explains how to do version control when creating a new database, but not when it is already old and relatively big.
The General Process
We create a baseline for a particular version (say, v1.0). A baseline includes one complete schema creation script, as well an upgrade script from allowed previous versions, if any (more on that in a moment). So for v1.0, we'd have just one script:
baseline-v1.0.sql
From that baseline, we create incremental change scripts as we work from the previous baseline. These scripts are created in a way that they are reentrant, so that they can be run safely multiple times (where the first time only does any actual work; see the next paragraph on a suggestion how). We just create a file for each change script with the baseline name and a timestamp (which we call the version). So for example, say we create two change scripts after a baseline. We'd have the following files:
baseline-v1.0.sql (for creating new installations)
baseline-v1.0-201211071220.sql (created on Nov. 7, 2012 at 12:20 PM UTC)
baseline-v1.0-201211122019.sql (created on Nov. 12, 2012 at 8:00 PM UTC)
We create a schema_version table that has two columns: baseline and version. baseline is some label (such as v1.0 mentioned above), and version is just a timestamp of when the change script was created (we chose to do this because creating arbitrary version numbers created annoying administrative overhead, where a timestamp was easy to use). So before running the change script, we check to see if the change script has been applied yet, by querying for it by baseline and version. If it's already present, just return out of the script or whatever. Otherwise, apply the change and insert into the schema_version table to mark the change script completed.
Example change script:
-- Created by <developer> on Nov. 7, 2012 at 12:20 PM UTC
declare #schema_baseline varchar(10), #schema_version varchar(12)
set #schema_baseline = 'v1.0'
set #schema_version = '201211071210'
if exists (select 1 from schema_version where baseline = #schema_baseline and version = #schema_version = #schema_version) return 0
-- begin change script
-- place your schema changes here
-- end change script
insert into schema_version(#schema_baseline, #schema_version)
Now, when we actually install the software, we run the relevant baseline script. As we upgrade that version, we just apply the change scripts in order.
When we hit a significant milestone in our product development phase, we create a new baseline. So, we create a new baseline script (again, this is a snapshot of the DB as a baseline), plus an upgrade script from the previous baseline. So let's say we have a new baseline, v2.0, we'd have the following files:
baseline-v2.0.sql (for creating new installations)
baseline-v2.0-upgrade-v1.0.sql (for upgrading from v1.0)
Then the process continues.
How We Apply Changes
The scripts are all kept in source control. We do have a tool that packages these files and automatically upgrades databases, which our support and installation teams use. The tool figures out the current baseline of the target database, and asks the user if they wish to upgrade to the baseline in the package. If they do, and there is a valid upgrade path from the current version, it applies the upgrade script, and updates the schema_version.baseline, and deletes all entries for change scripts from the previous baseline. If the database is new, it applies the regular baseline script. Either way, after the baseline is achieved, it applies all change scripts from the baseline that are present in the package, one at a time, in order, in a transaction. If a particular change script fails, it rolls back the last set of changes and errors out. We look at the log, fix any issues, then rerun the package again. At that point, it should just pick up at the last change script that succeeded, saving time.
Automation and Diff Tools
We do not allow diff tools to upgrade production databases directly. It's just too risky. We do use diff tools, of course, to help create our upgrade and change scripts, but once we have them, we comb through them, massage them, test them, etc., then create the upgrade or change script according to the specs above. We do use tools/shell scripts to create the change script files and put the boiler plate schema_version checking.
Caveats
It's actually pretty straight-forward and it works well. The only time it really gets tricky is with branches. For the most part, branches are handled well. If we need a change script for a particular branch's work, it will fold into the mainline very well once we merge the branch back in. No problem. Where it gets tricky is when two branches try to do similar things, or where one branch relies on another. That's mostly a process and planning issue, though. If we get stuck in such a situation, we just create a new baseline (say v2.1), then update the branches accordingly.
Another thing to keep in mind is if an installation wants to be upgraded from one baseline to another, it has to apply all outstanding changes for the current baseline, before we upgrade to the new one. In other words, we don't let installations jump right from where ever they are to the next baseline (unless, of course, they're already at the most recent version for the current baseline).
I would recommend SQL Server Data Tools and/or a Visual Studio SQL database project. It will reverse engineer your existing DB to code(sql) files that can be version controlled and gives many other niceties (publishing, comparison, etc)
We developed SQL Source Control specifically to solve the problem you describe. It extends SSMS to provide a link between your SQL Server schema objects (and static data) and your existing source control system.
http://www.red-gate.com/products/sql-development/sql-source-control/
If you need any more information, we'd be very pleased to help (contact support#red-gate.com)
There have been many discussions regarding this topic on many developer forums.
What I have done and found to be the simplest and cleanest way to do is this:
Extract every DB object's DDL into its own file, indexes and PKs can go in the same file as the table they belong to. FKs, procedures, views, triggers, anything that can go across multiple tables go in their own file.
Organize the DDL files in dirs per object type (e.g. table, procedure, trigger, view etc.)
For tables holding static reference data (e.g. zip code or state), have a separate file with a bunch of insert statements
Check this directory structure into whatever version control you are using
Write a script that will traverse this directory structure that images your DB, diff it against the actual DB you point to (extracting the schema from the system tables) and apply the diffs using ALTER TABLE statements
In case you have data transformations between releases, e.g. in v1 you had a field FirstAndLastName and in v2 you decided to split it into FirstName and LastName, you will have some bulk data migration/processing statement.
I have successfully managed DB changes in several jobs using several different RDBMSs. I usually use Perl for the script that diffs the DB schema and the DDL files in your image. There are some assumptions to this method and one of them is that you never make any changes to the DB directly in the DB but in your DDL files and then run the script to apply it. If you do it the other way, they will be undone when you run the script. So it requires some team agreement and discipline. Your milage may vary.
Now, if there is a FOSS tool out there that will do this for you, by all means use that rather than devising your own. I've been doing things this way for more than 10 yrs
Our Sql Historian source control system can help folks with this problem, especially in the situation you mention where teammates"forget" to check in code after they've updated the server.
It sits in the background and records all changes made to your db objects into source control, without users needing to check anything in. Think of it like an airplane blackbox recorder, staying out of the way until you need it.
I have the following scenario:
I'm starting development of a long project (around 6 months) and I need to have some information on the database in order to test my features. The problem is that right now, I don't have the forms to insert this information (I will in the future) but I need the information loaded on the DB, what's the best way to handle this? Specially considering that once the app is complete, I won't need this process anymore.
As an example, lets say I have tasks that need to be categorized. I've begun working on the tasks, but I need to have some categories loaded on my db already.
I'm working with Rails 3.1 btw.
Thanks in advance!
Edit
About seeds:I've been told that seeds are not the way to go if your data may vary a bit, since you'd have to delete all information and reinsert it again. Say.. I want to change or add categories, then I'd have to edit the seeds.rb file, do my modifications and then delete and reload all data...., is there another way? Or are seeds the defenitely best way to solve this problem?
So it sounds like you'll possibly be adding, changing, or deleting data along the way that will be intermingled amongst other data. So seeds.rb is out. What you need to use are migrations. That way you can search for and identify the data you want to change through a sequential process, which migrations are exactly designed for. Otherwise I think your best bet is to change the data manually through the rails console.
EDIT: A good example would be as follows.
You're using Capistrano to handle your deployment. You want to add a new Category, Toys, to your system. In a migration file then you would add Category.create(:name => "Toys") or something similar in your migration function (I forget what they call it now in Rails 3.1, I know there's only a single method though), run rake db:migrate locally, test your changes, commit them, then if it's acceptable deploy it using cap:deploy and that will run the new migration against your production database, insert the new category, and make it available for use in the deployed application.
That example aside, it really depends on your workflow. If you think that adding new data via migrations won't hose your application, then go for it. I will say that DHH (David Heinemeier Hansson) is not a fan of it, as he uses it strictly for changing the structure of the database over time. If you didn't know DHH is the creator of Rails.
EDIT 2:
A thought I just had, which would let you skip the notion of using migrations if you weren't comfortable with it. You could 100% rely on your db/seeds.rb file. When you think of "seeds.rb" you think of creating information, but this doesn't necessarily have to be the case. Rather than just blindly creating data, you can check to see if the pertinent data already exists, and if it does then modify and save it, but if it doesn't exist then just create a new record plain and simple.
db/seeds.rb
toys = Category.find_by_name("Toys")
if toys then
toys.name = "More Toys"
toys.save
else
Category.create(:name => "More Toys")
end
Run rake db:seeds and that code will run. You just need to consistently update the seeds.rb file every time you change your data, so that 1) it's searching for the right data value and 2) it's updating the correct attributes.
In the end there's no right or wrong way to do this, it's just whatever works for you and your workflow.
The place to load development data is db/seeds.rb. Since you can write arbitrary Ruby code there, you can even load your dev data from external files, for instance.
there is a file called db/seeds.rb
you can instantiate records using it
user1=User.create(:email=>"user#test.com",
:first_name=>"user",
:last_name=>"name",
:bio=>"User bio...",
:website=>"http://www.website.com",
:occupation=>"WebDeveloper",
:password=>"changeme",
:password_confirmation=>"changeme",
:avatar => File.open(File.join(Rails.root, '/app/assets/images/profiles/image.png'))
)
user2=User.create(:email=>"user2#test.com",
:first_name=>"user2",
:last_name=>"name2",
:bio=>"User2 bio...",
:website=>"http://www.website.com",
:occupation=>"WebDeveloper",
:password=>"changeme",
:password_confirmation=>"changeme",
:avatar => File.open(File.join(Rails.root, '/app/assets/images/profiles/image.png'))
)
Just run rake db:seed from command line to get it into the db