If your application needs to handle a large, long-lived set of interrelated data elements, you can confidently place it in a relational database. In the past, there were few relational DBMSs; they were complex, expensive to maintain, and clunky beasts. Those times are gone. Today, finding a relational DBMS is not difficult: it is quite possible that a relational DBMS or even two are already installed on your machine. Some very advanced relational DBMSs, such like MySQL and PostgreSQL, are available in source code, so the question of costs it is no longer worth buying them. Moreover, the so-called “embedded database systems” can be integrated into your application as libraries, almost requiring no configuration and administration; two such examples are interesting open-source DBMS, SQLite and HSQLDB. Such systems are extremely efficient.
If your application’s data does not fit into the system’s RAM, the indexed table of a Relational DBMS will work several orders of magnitude faster than the associative arrays of the language library, where the bottleneck will be page loading. virtual memory. The capabilities of modern databases can be easily scaled up as your needs grow. With the right approach, you will be able to scale the embedded database to a larger database if this will be needed. Then you will be able to transition from a free open-source base to a commercial system offering more advanced support or possibilities.
Having studied SQL well enough, you will enjoy creating applications built around databases. Once the normalized data is stored in the database, you can easily retrieve actual information about this data using clearly formulated SQL queries; there is no need to write complex code for this. Similarly, complex changes can be made to such datasets with a single SQL command. For one-time modifications, such as when it is necessary to change the way stored data is organized, there is no need to write code – it is sufficient to run a direct SQL access application to the database. This interface will also allow experimenting with queries without the edit-compile cycle of regular programming languages.
Another advantage of code oriented towards the use of Relational DBMS is the support for relationships between data elements. You can describe constraints that ensure data integrity, which will help avoid the risk of dangling references if you forget to update your data in edge cases. For example, a constraint can be formulated such that when a user is deleted, all messages sent by that user will also be deleted.
You can also create quick connections between the records stored in the database at any time by simply generating an index. It is not necessary to conduct costly and extensive refactoring of class fields. Moreover, when the code is built on a database, other applications can safely access this data. Thanks to this, it is easy to add parallel processing to your application and write its individual parts using the most suitable languages or platforms. For example, you can write the XML server of the web application in Java, some audit scripts in Ruby, and the visualization interface using Processing.
Finally, it should be remembered that the Relational DBMS will make every effort to optimize your SQL queries, allowing you to focus on the functionality of your application rather than fine-tuning algorithms. More advanced databases are even capable of taking advantage of multi-core processors, and all this without any involvement from you. As you The improvement of technologies will increase the performance of your application.