How many types of databases do we have?

A database is a place to store and store system data. In terms of categorization, the database or database is divided into two categories. SQL and NoSQL. The difference between these two types is through their construction, the type of information stored on them, and the way the information is stored. SQL databases are relational and have a specific structure, such as contact lists on mobile. NoSQL non-relational databases behave document-based. Like folders, each of which contains the information of a particular person. I, Arslan Mirbzergi, in the following article, I’m going to tell you the differences between these two databases, along with the features of each for you in simple language.

SQL relational databases:

The big difference between the two databases we mentioned in the previous paragraph is how each one organizes the data. The data classification method is designed in strict SQL databases. So that the data in this database or database is very regularly categorized. This category model was developed by IBM in 1970. Data in databases can have a number of different tables. In each of these tables, there are a number of rows and columns, and in rows, items, and in columns, data about each item is placed. In reviewing the database, the relationship between the table and the type of fields is called schema.

Before entering any data into the SQL database in the database or database, it is better to first provide an accurate definition of schema. The essential condition for the proper functioning of a database is the correct design. If the schema design is incomplete or poor, there will be inconsistencies in the data and if you add the new item to the database, you will have problems and even need to edit all the database data. The correct design of schema is vital, especially for businesses where data is very important (such as banks).

Why do we use the SQL relational database?

SQL banks are used in databases for a variety of reasons. In general, if your database is NoSQL and does not contain ACID or ACID does not matter in it, and therefore you are faced with data incompatibility in your database or if there is no change in your data, the best option for you is to use SQL databases. Postgres and MySQL are two well-known databases with this structure. These two databases are highly used in open source or web applications due to their structural similarity to each other, as well as their style and compactness. Although they use different algorithms in data transfer and storage speeds, they have almost the same speed.

The Postgres database has more features than MySQL and is therefore very suitable for open Source applications. It’s also easier for programmers dealing with oracle or Microsoft SQL than MySQL. On the other hand, MySQL should not be forgotten. In fact, the Postgres database is designed to fix the flaws in MySQL to the point that Clustering and ACID are better performed in Postgres than MySQL. If we want to make a short comparison between Postgres and MySQL, we can express it in the following table format.

Each of the Postgres and MySQL databases has disadvantages and advantages, and the choice of each project depends on the purpose of the project, but according to the points mentioned, the use of Postgres in the projects seems more appropriate.

NoSQL non-relational database:

We explained above that we need to build schema before entering any data into the SQL database. But suppose your data is messy or not clearly specified. In this case, instead of editing data to build schema, you can use another database called non-relational database or NoSQL. This type of database is much more flexible than the SQL database and you can enter all the relevant information together in a specific section.

NoSQL databases in the database, unlike SQL databases, store them in the document instead of storing data in the table. This method is very convenient for storing unorganized data, such as images or articles, in a document. On the other hand, using these NoSQL databases will also make it easier to search among data. It is worth noting that these databases require more memory and higher processing power in the database than SQL banks.

Why do we use NoSQL relational databases?

The use of NoSQL databases in the database also has a variety of reasons. You cannot use SQL banks if your data is too large or large. In this case, the best way is to use NoSQL banks. You can store your data in noSQL databases in the database, regardless of volume, type of data, as well as without applying any organization.

Another advantage of using NoSQL banks is storing data on the database cloud. This advantage saves database space. Of course, to increase the performance of this model of data storage, it is better to store data on different servers. NoSQL databases do not use schema so the time to build a project by you will be significantly reduced.

NoSQL Relational Database Types

In the table below are 4 models of NoSQL databases along with important features of each.

In the Key-Valuemodel database, data containing keys and values are stored in an unstructured path. Cassandra, Azure, LevelDB and Riak are examples of this type of database. Column Store banks store data in a column or Wide-Column method in the database. In this method, columns are used to store data, which gives the user the highest efficiency. Hbase, BigTable and HyperTable can be cited as examples of this type of bank.

In Document banks, storing information such as Key-Value databases is more complex. The data stored in this model is stored in the form of a document with its own key. MongoDB and CouchDB are examples of this type. Finally, Graph Databaseis one of the best ways to store related data together in the database. This model includes Polyglot and neo4j.

General differences between SQL and NoSQL databases:

If we want to headline the differences between these two types of databases, we can state as follows:

  1. SQL banks are known as relational databases and NoSQL banks are known as non-relational databases.
  2. Storing information in SQL banks is in tables and columns and in the NoSQL database in documents, key-values, graphs and wide-column.
  3. Schema is not required to enter data into the NoSQL bank, unlike SQL banks.
  4. SQL banks emphasize ACID and NoSQL banks on the implementation of the CAP process.
  5. SQL databases are more suitable in an environment such as applications where high data volumes are moved.
  6. For scalability of relational databases, it is necessary to change the nature of the database. It’s also very time-a-time. If any changes to NoSQL databases are much easier.
  7. SQL databases usually have good support. Even some companies formally and exclusively provide support services for these databases. In contrast, only some NoSQL databases have the right support. Other models of these banks do not have official support and their support is done solely in forums on the Internet.

And in the end,

In general, and according to the description given in this article, it is better to use a database such as SQL. If we need specific operations or features in the project, use the combination of NoSQL databases suitable for SQL databases. Mirbazorgi’s website aims to help you learn and fix your problems by providing articles and practical experiences. Email me if you have any questions.