We have a SaaS application where each tenant has its own database in Postgres. How would I apply a patch to all the databses? For example if I want to add a table or add a column to a table, I have to either write a program that loops through all databases and execute a SQL against them or using pgadmin, go through them one by one.
Is there smarter and/or faster way?
Any help is greatly appreciated.
Yes, there's a smarter way.
Don't create a new database for each tenant. If everything is in one database then you only need to alter one database.
Pick one database, alter each table to have the column TENANT and add this to the primary key. Then insert into this database every record for all tenants and drop the other databases (obviously considerably more work than this as your application will need to be changed).
The differences with your approach are extensively discussed elsewhere:
If you don't put everything in one database then I'm afraid you have to alter them all individually, and doing it programatically would be simplest.
At a higher level, all multi-tenant applications follow one of three approaches:
I usually find that developers use the following criteria when they evaluate these different approaches.
Isolation: Since you can put each tenant into its own database in one hand, and have tenants share the same table on the other, this becomes the most apparent dimension. If you provide your users raw SQL access or you're in a regulated industry such as healthcare, you may need strict guarantees from your database. That said, PostgreSQL 9.5 comes with row level security policies that makes this less of a concern for most applications.
Extensibility: If your tenants are sharing the same schema (approach #3), and your tenants have fields that varies between them, then you need to think about how to merge these fields.
This article on multi-tenant databases has a great summary of different approaches. For example, you can add a dozen columns, call them C1, C2, and so forth, and have your application infer the actual data in this column based on the tenant_id. PostgresQL 9.4 comes with JSONB support and natively allows you to use semi-structured fields to express variations between different tenants' data.
Scaling: Another criteria is how easily your database would scale-out. If you create a tenant per database or schema (#1 or #2 above), your application can make use of existing Ruby Gems or [Django packages][1] to simplify app integration. That said, you'll need to manually manage your tenants' data and the machines they live on. Similarly, you'll need to build your own sharding logic to propagate foreign key constraints and ALTER TABLE commands.
With approach #3, you can use existing open source scaling solutions, such as Citus. For example, this blog post describes how to easily shard a multi-tenant app with Postgres.
it's time for me to give back to the community :) So after 4 years, our multi-tenant platform is in production and I would like to share the following observations/experiences with all of you.
We used a database per each tenant. This has given us extreme flexibility as the size of the databases in the backups are not huge and hence we can easily import them into our staging environment for customers issues.
We use Liquibase for database development and upgrades. This has been a tremendous help to us, allowing us to package the entire build into a simple war file. All changes are easily versioned and managed very efficiently. There is a bit of learning curve here an there but nothing substantial. 2-5 days can significantly save you time.
Given that we use Spring/JPA/Hibernate, we use a technique called Dynamic Data Source Routing. So when a user logs-in, we find the related datasource with a lookup and connect them to the session to the right database. That's also when the Liquibase scripts get applied for updates.
This is, for now, I will come back with more later on.
Well, there are problems with one database for all tenants in our case for sure.
The backup file gets huge and becomes almost not practical hard to manage
For troubleshooting, we need to restore customer's data in our dev env, we just use that customer's backup file and usually the file is not as big as if we were to use one database for all customers.
Again, Liquibase has been key in allowing to manage updates across all the tenants seamlessly and without any issues. Without Liquibase, I can see lots of complications with this approach. So Liquibase, Liquibase and more Liquibase.
I also suspect that we would need a more powerful hardware to manage a huge database with large joins across millions of records vs much lighter database with much smaller queries.
In case of problems, the service doesn't go down for everyone and there will be limited to one or few tenants.
In general, for our purposes, this has been a great architectural decision and we are benefiting from it every day. One time we had one customer that didn't have their archiving active and their database size grew to over 3 GB. With offshore teams and slower internet as well as storage/bandwidth prices, one can see how things may become complicated very quickly.
Hope this helps someone.
--Rex
