Implementing a Large-scale Relational Database in a Distributed Database System.

Implementing a Large-scale Relational Database in a Distributed Database System.

In this tutorial, we'll learn Implementing a Large-scale Relational Database in a Distributed Database System.

First we need to understand the difference between the centralized database and the distributed database. So basically, with the centralized database, there is one single database and located at one side of our network. In the distributed database there are two or more database files located on the network (in different departments and different sections) and they need to be synced at the end of the day.

The advantage of the centralized database is since there is only one database file you always are getting a complete view of the system. you’re seeing as it’s being updated. you’re seeing the changes that are being made when you update and change it. everyone has access to that.

The advantage of a distributed database is because there are multiple database files you won’t interfere with each other if someone’s accessing the specific record. After all, you’re working on a different copy. there might be faster if you’re on a larger network because the actual file might be saved in a location that is more localized to where your workspace is. also, if one site fails the complete system won’t go down because you still got other database files to work from maybe not your specific department but still there are existing files that can be used by the company.

The disadvantages of a centralized database are can led to bottlenecking with many people accessing one file it could slow down the bandwidth that can slow down the function of the actual program because everyone trying to access data you might have to wait till someone’s finished using the actual database so you can fill in your entry can slow down productivity.

The disadvantages of the distributed database are that you’ve got to synchronize, and synchronizing takes time. because all the databases have to be synchronizing the data that they all have matching data at the end of the day. The other issue can be data and needs to be replicated so you need more than one file so which means more file sizes are being used up. It could also mean people entering the same data getting in the same day because they’re not knowing that it’s being put in on different sites.

The advantage and disadvantage of DDBMS are discussed here clearly.

data data-science distributed-systems database data-engineering

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