Relational Versus Non-Relational Databases

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When we develop apps or services, we usually come to a choice which looks like relational vs. non-relational databases. The difference between them is mainly about the type of data supported, the way they are developed and the method of storing data.

Relational databases store structured data that usually represent real objects. For example, the list of goods in a basket or personal data which are grouped in preliminary formatted tables. In order to deal with relational databases, we use universal SQL language.

Non-relational databases differ. For example, such a database can store data about objects with different types of attributes. Data that will be stored in separate related tables in the relational database can be stored in a single table in a non-relational database. Such databases are also called NoSQL due to the fact we use specified commands and queries to deal with them.

Relational Databases

Relational databases represent centralized table storages providing safe and simultaneous access to the information from multiple users. In the table lines, part of the fields contain data related to the record, and another part contains links to the records of other tables. Thus, the direct relationship between the fields is the must for relational databases.

Each record of the table has the same structure. For example, in a table containing a description of the car, all the records will have the same set of fields: manufacturer, model, color, etc. Such a table can be easily visualized.

A relational model provides information and structural independence. Changing the content of the one record doesn’t lead to the change of the content of another record, and the change of the database structure may not lead to the recompilation of the apps addressing it.

When dealing with relational databases there are issues with SQL standards which are different for each separate relational database. A single database realizes a specified standard of SQL plus a set of unique commands which makes it difficult for developers to come from one DB to another. Thus, one has to make a choice between the transferability and efficiency.

In order to provide the best transferability, one has to adhere to the principle of exploitation the minimum set of commands supported for each database. For the provision of the maximum efficiency, one has to use the most effective commands for each database separately. 

Pros and Cons

There is a list of advantages for the relational databases:

  • Simplicity. There is only one informational construction in the relational database. It standardizes the table data representation which is common for users.
  • Data independence. When you need to change the structure of the relational database it leads to the minimum changes in the application.
  • Along with advantages, there are a couple of shortcomings when you deal with relational databases:
  • An approach leads to decrease of program execution speed.
  • Significant storage consumption for the representation of the relational database. 

Non-Relational Databases

Non-relational databases are databases that do not comply with prevailing standards of data storage. Usually, they do not have a strict structure and typically do not contain tables or links within them. There are several types of non-relational databases that are defined by the scalability, data model and queries and the data storage system. 

Pros and Cons

Non-relational databases have unique networking APIs which are usually represented as cut SQL version. There is a list of advantages for such databases:

  • Development simplicity. Most of such non-relational databases have fewer functions than relational ones. Thus, the one who is working with such a database can operate with the system using the limited number of queries. It makes it easier to work with NoSQL databases.
  • Simple syntax – fewer mistakes. Most of the developers use the ORM technology to deal with queries to databases when dealing with the relational database. Such a method is rather efficient, but it demands more skills and more profound knowledge, while the queries for NoSQL databases are rather primitive which is decreasing a learning curve necessary to work with them.

There are also shortcomings for non-relational databases one needs to consider. Most of those can be fatal in the long-term perspective:

  • The app is too tied to the specified DBMS (database management system). When you deal with relational databases, you can use universal SQL which works for all kind of relational databases, so the user doesn’t have to rewrite the whole code in case of changing the DBMS. On the other hand, even if there are two almost similar NoSQL systems, they have too many different standards in API and query specifications.
  • The limited capacity of the integrated query language. SQL used for relational databases has multiple standards. It is a potent and complicated tool to operate with data and make reports. Almost all of the query languages and API methods for NoSQL were created on the basis of SQL functions. As a matter of fact, they are less functional.
  • Low value and diversification – it is much easier to find skilled SQL developers as it is used widely.

Non-Relational Databases vs. Relational

Let’s compare the advantages and disadvantages of reviewed above database types:

  • Structure and types of data – relational databases exploit standardized data types while non-relational databases allow using any data types.
  • Queries – regardless of license type relational data types mainly comply with the SQL standards so that you can retrieve data with SQL. Non-relational databases use specified query methods.
  • Scalability – both of these database types can be easily vertically scaled. However, non-relational are better for horizontal scaling.
  • Reliability – when it comes to the data security relational databases are still better.
  • Support – relational databases are very popular, and there are many options delivered. In case of issues arisen it is much easier to find a solution for relational databases.
  • Storage and access to complicated data structures – relational databases are much better for dealing with complicated data structures.

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