![]() But, in our case, By splitting databases based on each subsystem, it's much easier to scale each database without affecting all the other databases. When it comes to scaling, It almost often doesn't matter if you're using Single or Multiple Databases. When each sub system in split into a distinct database, the performance will be much better because each database serves a specific sub-system(Of course since they're part of the bigger system, they do provide cross data). So data integrity is not a problem at all as long as the designer knows what they're doing in terms of how the databases communicate and how they are related.įrom performance point of view, these systems are often used by Big companies and putting such in one database bring some performance risks because that database will have to serve all of those systems at once. Firstly, Databases are designed(via Schemas) before they are implemented. ![]() Would you really want to use a single database for this? You probably could, If you want.īut the best case scenario is multiple databases. and all these packages belong to one complex System. Imagine a system comprised of Inventory, Accounting, Engineering processes (E.g. One could argue that an approach is chosen to serve a need/requirement. Like any other approach in Software, each one comes with its own Pros and Cons. Of course, it's more complex than this, but the basics do apply. This way if any one machine experiences a failure, you lose no data, and at worst you'll have to restart a query. If you're going to use multiple machine for reliability and enhanced performance, perhaps you can structure them so that you have a master server with multiple warm/hot standby machines which could also be used to distribute queries across. the hardware which is used to serve the data.īreaking the database across multiple machines does you no good for the many reasons explained by the other answers in this topic. I think it's important to split the notion of "the database" into two pieces: the schema and data vs. What is the likelihood that a hardware failure is going to impact your application? If there is a 0.1% chance that any particular server may die on a particular day, are your chances better or worse that you're going to be impacted by a hardware failure when increasing the number of machines you're dependent upon? Thought experiment: Instead of dividing your database into seven pieces, split it instead into 7,000 pieces.
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