The system I'm designing has a set of reference tables that rarely have to be updated. New databases will be constantly started to process files that will have to query that information.
What's the best arrangement for coordinating communication between that set of information and the work database? I certainly don't want to duplicate that set of reference information in every new work database. The work databases will likely be deleted once their work is completed.
Related
We are involved in quite a new development in which we are remaking our current web shop platform.
In the current platform we do not use EF6 neither other ORM but store procedures to access to the db, but in the new building is what we do.
We have a doubt regarding database design of the new platform. In the current platform we use several different databases depending on the content of them.
For example, we have dedicated databases to store information for products catalogs other dedicated db for handling orders.
Currently all data access is done through stored procedures, so we have no problem with the links between different databases.
The problem appears to us now when we have started to use EF6. In this case each DB is associated with a context and it is not possible to know data from one context to another
unless we implement directly in the source code these relationships using various contexts. It looks like these means we will lose the power of EF6.
The questions we have are:
Is it a bad design maintaining different databases for the same application using EF6?
in case this is a poor design and choosing for a single database, is the performance going to be optimum even driving hundreds of tables (almost 1000) with several TBytes of information?
in the other hand, in the case of opting for the design in which several bbdd appear (it would be much better in our case), what is the best way to handle them EF6?
Thank you very much for your help!
First of all EF is not written to be cross database. You can't write cross database (cross context) queries, lazy load does not work and so on.
This is a big limitation in your case.
EF could work with several schema (actually I don't use it and I don't like it but is just my opinion).
You can use your stored procedures with EF but as I understand you are thinking to stop to use them.
In my experience I wrote several applications with more than one database but the use of the different databases was very limited. In this cases I use cross database views (i.e. one database per company and some common tables with views in company databases that selects data in common tables). In your case, if the tables are sharded everywhere I don't think this is a way you can choose.
So, in my opinion you could change the approach.
If you have backups problems you could shard the huge tables (I think facts tables and tables with pictures) and create cross database views. BTW, also, cross database referential integrity is not supported in SQL Server so you need to write triggers to check it.
If you need to split different application functions (i.e. WMS, CRM and so on) you can use namespaces without bothering about how tables are stored in the DB.
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:
What problems will I get creating a database per customer?
What are the advantages of using a single database for EACH client?
Multiple schemas versus enormous tables
Practicality of multiple databases per client vs one database
Multi-tenancy - single database vs multiple database
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:
One tenant's data lives in one database,
One tenant's data lives in one schema, or
Add a tenant_id / account_id column to your tables (shared schema).
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
I have recently moved to MongoDB part of the back-end of a web app, the web app itself is a validation tool, and the workflow looks like:
the user uploads a file (typically hundreds of thousands of lines)
the validator checks it outputting a lot of messages (possibly more than one per line)
...and finally provide a few statistics
I modelled my application so that each user has it's own DB containing:
The file (saved through GridFS)
A collection containing the messages (possibly over a million lines, in some cases)
A collection with the statistics
We have a few hundreds of users, so MongoDB will end up having a few hundreds DBs.
Of course I could have hold all the data in the same DB, using namespaces to separate data from different users. However I felt it was handy to send the DB in the connection URI, and I found more intuitive to issue a "drop database" statement to purge a user, rather than searching and removing its data in the large DB.
I am pretty new to MongoDB, so my question is: is there any drawback in having several DBs in the same MongoDB instance? Or is there any special consideration that I should give to the problem?
I'm not familiar with MongoDB specifically. In general, openning a connection to a database is a relatively slow operation and ties up system resources. Whether this is enough to matter in your case I can't say.
Having a different db for each user would make it difficult to perform queries that access data for multiple users. Maybe you have no need to do this.
Still, I would think it would be a whole lot simpler in general to just put a user id in each record rather than create a separate database. What's the gain of separate databases? Okay, deleting a user means saying "drop database". But deleting a user from a single database should mean saying "delete from tableX where user=?; delete from tableY where user=?" etc for however many relevant tables you have. I can't imagine it's hundreds, right? Maybe half a dozen lines of code or so?
I am new to the PostgreSQL database. What my visual c++ application needs to do is to create multiple tables and add/retrieve data from them.
Each session of my application should create a new and distinct database. I can use the current date and time for a unique database name.
There should also be an option to delete all the databases.
I have worked out how to connect to a database, create tables, and add data to tables. I am not sure how to make a new database for each run or how to retrieve number and name of databases if user want to clear all databases.
Please help.
See the libpq examples in the documentation. The example program shows you how to list databases, and in general how to execute commands against the database. The example code there is trivial to adapt to creating and dropping databases.
Creating a database is a simple CREATE DATABASE SQL statement, same as any other libpq operation. You must connect to a temporary database (usually template1) to issue the CREATE DATABASE, then disconnect and make a new connection to the database you just created.
Rather than creating new databases, consider creating new schema instead. Much less hassle, since all you need to do is change the search_path or prefix your table references, you don't have to disconnect and reconnect to change schemas. See the documentation on schemas.
I question the wisdom of your design, though. It is rarely a good idea for applications to be creating and dropping databases (or tables, except temporary tables) as a normal part of their operation. Maybe if you elaborated on why you want to do this, we can come up with solutions that may be easier and/or perform better than your current approach.
I am using Self Tracking Entities with the Entity Framework 4. I have 2 databases, with the exact same schema. However, tables in one database will be added to/edited etc (and I mean data will be added/edited, not the actual table definitions) and at certain points of the day I will need to synchronize all the changes between this database and the other database.
I can create a separate context for both of them. But if I read a large graph from one database, how can I update the other database with the graph? Is there an easy way?
My database model is large and complex and fully relational. So it would be a big job to go through every single entity and do a read from the other database to see if it exists or not, update/insert it if need be, and then carry this on through the full object graph!
Any ideas?
This is not a use case for EF. In EF you will have to do exactly what you've described. Self tracking entities are able to track changes to these object instances - they know nothing about changes made to their own database over time and they will not know anything about state of your second database as well.
Try to look at SQL server native features (including mirroring, transaction log shipping or SSIS) and MS Sync framework. Depending on your detailed requirements these tools can suite you better.