Little question, I'm developing a saas software (erp).
I designed it with 1 database per account for these reasons :
I make a lot of personalisation, and need to add specific table columns for each account.
Easier to manage db backup (and reload data !)
Less risky : sometimes I need to run SQL queries on a table, in case of an error with bad query (update / delete...), only one customer is affected instead of all of them.
Bas point : I'm turning to have hundreds of databases...
I'm hiring a company to manage my servers, and they said that it's better to have only one database, with a few tables, and put all data in the same tables with column as id_account. I'm very very surprised by these words, so I'm wondering... what are your ideas ?
Thanks !
Frederic
The current environment I am working in, we handle millions of records from numerous clients. Our solution is to use Schema to segregate each individual client. A schema allows you to partition your clients into separate virtual databases while inside a single db. Each schema will have an exact copy of the tables from your application.
The upside:
Segregated client data
data from a single client can be easily backed up, exported or deleted
Programming is still the same, but you have to select the schema before db calls
Moving clients to another db or standalone server is a lot easier
adding specific tables per client is easier (see below)
single instance of the database running
tuning the db affects all tenants
The downside:
Unless you manage your shared schema properly, you may duplicate data
Migrations are repeated for every schema
You have to remember to select the schema before db calls
hard pressed to add many negatives... I guess I may be biased.
Adding Specific Tables: Why would you add client specific tables if this is SAAS and not custom software? Better to use a Postgres DB with a Hstore field and store as much searchable data as you like.
Schemas are ideal for multi-tenant databases Link Link
A lot of what I am telling you depends on your software stack, the capabilities of your developers and the backend db you selected (all of which you neglected to mention)
Your hardware guys should not decide your software architecture. If they do, you are likely shooting yourself in the leg before you even get out of the gate. Get a good senior software architect, the grief they will save you, will likely save your business.
I hope this helps...
Bonne Chance
Related
I've researched a lot for the best multi-tenant setup of an e-commerce project but could not find a fitting answer. I am leaning to use a shared database separate schema setup with either MySQL or PostgreSQL. The structure of the tables is the same for all the tenants. I really like that with that setup the application code doesn't need to provide an extra WHERE clause for every query, so it is very developer friendly!
Now you also have the shared schema approach and that is what I am currently using, but I feel this is bad for security and isolation purposes. I would like to move to a different solution.
The app will be used by +- 100 webshops (a tenant) this year and I expect it to grow to into the thousands. Webshops ranges from small to large, so it is important that I can later pick out a specific shops data and put it in it's own database server.
Since I don't have any experience with a separate schema setup I would like to know if this would benefit me. What issues might I have when walking that path? Especially with changes in the structure of the tables, this is what bothers me the most. What is the limit of schema's to use in a separate schema approach using PostgreSQL (I will have 100-1000 schemas) before it would be a pain to manage?
The following is my take
Blockquote
When using the SharedDatabase with same table for all tenants, isolation happening with tenantid column is easy because you always add a filter that says tenantid = LoggedInTenantId [LoggedInTenantId => set during login]. When you have a base method in your ORM like EF [I'm from .Net], this would auto append to any query that goes out of the code.
When you opt for shared Schema, if there is a use-case like sharing data between tenants [webshops], it is not feasible. Else, if you have an accountant that wants to audit a collection of tenant's and wants a dashboard to view the a/c statistics etc, it becomes impossible
With the scaling point of view, you can better go for a separate db per tenant if a single tenant or a collection of them wants to scale out. This will be better than managing schemas.
Consider the use-cases that you may have for your product and share here so that we can take this discussion forward.
HTH
Scenario:
Building a commercial app consisting in an RESTful backend with symfony2 and a frontend in AngularJS
This app will never be used by many customers (if I get to sell 100 that would be fantastic. Hopefully much more, but in any case will be massive)
I want to have a multi tenant structure for the database with one schema per customer (they store sensitive information for their customers)
I'm aware of problem when updating schemas but I will have to live with it.
Today I have a MySQL demo database that I will clone each time a new customer purchase the app.
There is no relationship between my customers, so I don't need to communicate with multiple shards for any query
For one customer, they can be using the app from several devices at the time, but there won't be massive write operations in the db
My question
Trying to set some functional tests for the backend API I read about having a dedicated sqlite database for loading testing data, which seems to be good idea.
However I wonder if it's also a good idea to switch from MySQL to SQLite3 database as my main database support for the application, and if it's a common practice to have one dedicated SQLite3 database PER CLIENT. I've never used SQLite and I have no idea if the process of updating a schema and replicate the changes in all the databases is done in the same way as for other RDBMS
Is this a correct scenario for SQLite?
Any suggestion (aka tutorial) in how to achieve this?
[I wonder] if it's a common practice to have one dedicated SQLite3 database PER CLIENT
Only if the database is deployed along with the application, like on a phone. Otherwise I've never heard of such a thing.
I've never used SQLite and I have no idea if the process of updating a schema and replicate the changes in all the databases is done in the same way as for other RDBMS
SQLite is a SQL database and responds to ALTER TABLE and the like. As for updating all the schemas, you'll have to re-run the update for all schemas.
Schema synching is usually handled by an outside utility, usually your ORM will have something. Some are server agnostic, some only support specific servers. There are also dedicated database change management tools such as Sqitch.
However I wonder if it's also a good idea to switch from MySQL to SQLite3 database as my main database support for the application, and
SQLite's main advantage is not requiring you to install and run a server. That makes sense for quick projects or where you have to deploy the database, like a phone app. For server based application there's no problem having a database server. SQLite's very restricted set of SQL features becomes a disadvantage. It will also likely run slower than a server database for anything but the simplest queries.
Trying to set some functional tests for the backend API I read about having a dedicated sqlite database for loading testing data, which seems to be good idea.
Under no circumstances should you test with a different database than the production database. Databases do not all implement SQL the same, MySQL is particularly bad about this, and your tests will not reflect reality. Running a MySQL instance for testing is not much work.
This separate schema thing claims three advantages...
Extensibility (you can add fields whenever you like)
Security (a query cannot accidentally show data for the wrong tenant)
Parallel Scaling (you can potentially split each schema onto a different server)
What they're proposing is equivalent to having a separate, customized copy of the code for every tenant. You wouldn't do that, it's obviously a maintenance nightmare. Code at least has the advantage of version control systems with branching and merging. I know only of one database management tool that supports branching, Sqitch.
Let's imagine you've made a custom change to tenant 5's schema. Now you have a general schema change you'd like to apply to all of them. What if the change to 5 conflicts with this? What if the change to 5 requires special data migration different from everybody else? Now let's imagine you've made custom changes to ten schemas. A hundred. A thousand? Nightmare.
Different schemas will require different queries. The application will have to know which schema each tenant is using, there will have to be some sort of schema version map you'll need to maintain. And every different possible query for every different possible schema will have to be maintained in the application code. Nightmare.
Yes, putting each tenant in a separate schema is more secure, but that only protects against writing bad queries or including a query builder (which is a bad idea anyway). There are better ways mitigate the problem such as the view filter suggested in the docs. There are many other ways an attacker can access tenant data that this doesn't address: gain a database connection, gain access to the filesystem, sniff network traffic. I don't see the small security gain being worth the maintenance nightmare.
As for scaling, the article is ten years out of date. There are far, far better ways to achieve parallel scaling then to coarsely put schemas on different servers. There are entire databases dedicated to this idea. Fortunately, you don't need any of this! Scaling won't be a problem for you until you have tens of thousands to millions of tenants. The idea of front loading your design with a schema maintenance nightmare for a hypothetical big parallel scaling problem is putting the cart so far before the horse, it's already at the pub having a pint.
If you want to use a relational database I would recommend PostgreSQL. It has a very rich SQL implementation, its fast and scales well, and it has something that renders this whole idea of separate schemas moot: a built in JSON type. This can be used to implement the "extensibility" mentioned in the article. Each table can have a meta column using the JSON type that you can throw any extra data into you like. The application does not need special queries, the meta column is always there. PostgreSQL's JSON operators make working with the meta data very easy and efficient.
You could also look into a NoSQL database. There are plenty to choose from and many support custom schemas and parallel scaling. However, it's likely you will have to change your choice of framework to use one that supports NoSQL.
I'll be soon developing a big cms where users can configure their website managing news, products, services and much more about their company.
Think about a shopify without the ecommerce part (at least for now).
The rdbms is MySQL and the user base will be about 150 (maybe bigger).
I'm trying to figure out which one of these two approaches would fit better.
DEDICATED DATABASE FOR EACH USER
PROS:
performance (and possible future sharding?): is querying smaller database with just your data better than querying a giant database with every user data?
easy "export my data" for users: I can simply dump their own db without fetching everything and putting it in some big encoded logical datastruct
SINGLE DATABASE FOR EVERY USER
PROS:
less general overhead
statistic: just one db to query to get and aggregate whatever I need
backup: one dump (not sure about this one because I've no experience in cluster dumping)
Which way would you go for? I don't think shopify created a dedicated database for any user registered... or maybe they did?
I'd like more experienced people than me to help me figuring out the best way and all the variables I can not guess right now because of my ignorance.
It sounds like you're developing a software-as-a-service hosted system, rather than a software package to distribute to customers for them to run on their own servers. In that case, in general, you will have an easier time developing and administering your service if you design it for a single database handling multiple users.
You'll be able to add new users to your system with data manipulation language (DML) rather than data definition language (DDL). That is, you'll insert rows for new users rather than create tables. That will make your life a LOT easier when you go live.
You are absolutely right that stuff like backups and aggregate reporting will be far easier if you have a single shared database.
Don't worry too much about the user data export functions. You'll have to develop software for those functions anyway; it won't be that hard to filter by user when you do the export.
But there's a downside you should consider to the single-database approach: if part of your requirement is to conceal various users' existence or data from each other, you'll have to be very careful to do this in your development. Will your users be competitors with each other? That could be tricky. You'll need to trust your in-house admin and support teams to refrain from disclosing one user's data to another by mistake (or deliberately). With a separate database per user, you'll have a smaller risk in that area.
150 users aren't many. Don't worry about scalability until you have a workload of paying customers. When that happens you can add MySQL server RAM, partitions, solid-state disks, replication, memcached, sharding, and all that other expensive and high-workload stuff. If you add those things before you go live, you'll just take longer and blow more money before you go live. Not good.
This is more of a conceptual question so variations on the stack are welcome should they be capable of accomplishing the same concept. We're currently on MySQL and expanding some services out into MongoDB.
The idea is that we would like to be able to manage a single physical database schema/structure so that adjustments, expansions etc. don't become overly cumbersome as the number of clients utilizing the structure grows into the thousands, tens of, hundreds of, etc. however we would like to segregate their data at this level rather than simply at the application layer to provide a more rigid separation. Is it possible to create virtual bins for each client using the same structure, but have their data structurally separated from one another?
The normal way would obviously be adding Client Keys to every row of data either directly or via foreign relationships, but given that we can't foresee with 20/20 how hacks on our system might occur allowing "cross client" data retrieval, I wanted to go a little further to embed the separation at a virtually structural level.
I've also read another post here: MySQL: how to do row-level security (like Oracle's Virtual Private Database)? which uses "views" as a method but this seems to become more work the larger the list of clients.
Thanks!
---- EDIT ----
Based on some of the literature suggested below, here's a little more info on our intent:
The closest situation of the three outlined in the MSDN article provided by #Stennie would be a single database, multiple-schema, however the difference being, we're not interested in customizing client schemas after their creation, we would actually prefer they remain locked to the parent/master schema.
Ideally the solution would keep each schema linked to the parent table-set structure rather than simply duplicating it with the hope that any change to the parent or master schema would be cascaded across all client/tenant schemas.
Taking it a step further, in a cluster we could have a single master with the master schema, and each slave replicating from it but with a sharded set of tenants. Changes to the master could then be filtered down through the cluster without interruption and would maintain consistency across all instances also allowing us to update the application layer faster knowing that all DB's are compatible with the updated schemas.
Hope that makes sense, I'm still a little fresh at this level.
There are a few common infrastructure approaches ranging from "share nothing" (aka multi-instance) to "share everything" (aka multi-tenant).
For example, a straightforward approach to your "virtual bins" would be to allocate a database per client using shared database servers. This is somewhere in between the two sharing extremes, as your customers would be sharing database server infrastructure but keeping their data and schema separate.
A database-per-client approach would allow you to:
manage authentication and access per client using the database's authentication & access controls
support different database software (you mention using both MySQL which supports views, and MongoDB which does not)
more easily backup and restore data per client
avoid potential cross-client leakage at a database level
avoid excessive table growth and related management issues for a single massive database
Some potential downsides would include:
having more databases to manage
in the case of a database where you want to enforce certain schema (i.e. MySQL) you will need to apply the schema changes across all your databases or support some form of versioning
in the case of a database which preallocates storage (i.e. MongoDB) you may use more storage per client (particularly if your actual data size is small)
you may run into limits on namespaces or open files
you still have to worry about application and data security :)
If you do some research on multi-tenancy you will find some other solutions ranging from this example (isolated DB per client on shared database server architecture) through to more complex partitioned data schemes.
This Microsoft article includes a useful overview of approaches and considerations: Multi-tenant SaaS database tenancy patterns.
I'm creating a multi-user/company web application in PHP & MySQL. I'm interested to know what the best practice is with regards to structuring my database(s).
There will be hundreds of companies and thousands of users of this web app so this needs to be robust. Each company won't be able to see other companies data, just their own. We will be storing mainly text data and will probably only be a few MB per company.
Currently the database contains 14 tables (for one sample company).
Is it better to put the data for all companies and their users in a single database and create a unique companyID for each one?
or:
Is it better to put each company's data in its own database and create a new database and table set for each new company that I add?
What are the pluses and minuses to each approach?
Thanks,
Stephen
If a single web app is being used by all the different companies, unless you have a very specific need or reason to use separate databases (it doesn't sound like you do), then you should definitely use a single database.
Your application will be responsible for only showing the correct information to the correct authenticated users.
Multiple databases would be a nightmare to maintain. For each new company you'd have to create and administer each one. If you make a change to one schema, you'll have to do it to your 14+.
Thousands of users and thousands of apps shouldn't pose a problem at all as long as you're using something that is a real database and not Access or something silly like that.
Multi-tenant
Pluses
Relatively easy to develop: only change database code in one place.
Lets you easily create queries which use data for multiple tenants.
Straightforward to add new tenants: no code needs to change.
Transforming a multi-tenant to a single-tenant setup is easy, should you need to change your design.
Minuses
Risk of data leak between tenants if coding is sloppy. Tenant view filters can in some cases be employed to reduce this risk. This method is based on using different database user accounts for different tenants.
If you break the code, all tenants will be affected.
Single-tenant
Pluses
If you have very different requirements for different tenants, several different database models can be beneficial. This is the best case for using a single tenant setup.
If you code sloppily, there's practically no risk of data leak between tenants (tenant A will not be able to access tenant B's data). In addition, if you accidentally destroy the schema of one tenant through a botched update, other tenants will remain unaffected.
Less SQL code when you don't need to take tenant ID values into account in your queries
Minuses
Database schemas tend to differentiate with time, often resulting in a nightmare. Using a database compare tool, you can alleviate this problem, but potentially many schemas need to be compared.
Including data from several databases in one query is typically complex, and often requires prepared statements.
Developing is hard, since you need to make the same changes to multiple schemas.
The same database entity can appear in many databases with different ID keys, resulting in confusion.
Transforming a single-tenant to a multi-tenant setup is very hard, should you need to change your design.
A single database is the relational way. One aspect from this perspective is that databases gather statistics about database usage and make heavy use of this. If you split things up you will be shooting yourself in the foot as the statistics will be fragmented.