Best Database For Node Js

What I always want when choosing my database management software is flexibility. It could improve it by creating a simpler and more intuitive web interface, but the first that comes to mind is the user experience of the application. There are many choices like standard MySQL, MariaDB and Percona for databases that can handle large sets of information. Although all have good practical results and do not take much to master them, I would still recommend using a different database for Node JS

Best Database For Node Js

SQL and NoSQL Databases

All computer calculations are related to data processing. They can be structured and unstructured. The former are placed in databases, where their description is stored, along with the information. You can often come across the terms “SQL” and “NoSQL” when talking about databases.

SQL is a processing technique that is used for processing relational and non-relational (NoSQL) databases.

The term “relational” comes from algebra. In databases, this means that relational database data is stored in the form of tables and rows. Non-relational databases store information in collections of JSON documents.

Relational databases use SQL, which stands for “Structured Query Language”. The structure of such databases allows you to link information from different tables using external keys (or indices), which are used to uniquely identify any atomic piece of data in each table. Other tables can refer to this external key to create a relationship between data parts and the parts pointed to by this foreign key.

Why do we need non-relational databases? Their main advantage is a high level of security and the ability to bypass hardware restrictions.

Now let’s take a look at the differences and similarities between SQL and NoSQL databases.

Language

Imagine a city where everyone speaks the same language. This language is used in all forms of communication and all business processes are built on it. The inhabitants of this city understand each other and explore the world around them only through this language. If the language suddenly changes in one place, everyone else will be confused.

Now imagine another city, where everybody speaks different languages at home. Everyone interacts with the world in different ways, there is no “universal” way of understanding and no sustainable organization of communication. If one changes something, it will not affect anyone else.

This example helps illustrate one of the main differences between SQL (relational) and NoSQL (non-relational) databases.

Relational databases use a structured query language to process and manipulate data. On the one hand, this is quite convenient: SQL is one of the most versatile and commonly used language options, so it is a safe choice. Also, it’s suitable for complex queries. On the other hand, there are certain limitations with this language. Before you start working with SQL, you need to use predefined schemas to define the data structure. In addition, all data must have the same structure. It’s like the first example said: a change in structure can result in complications and destroy the entire system.

In contrast, non-relational databases have flexible schemas for unstructured data. It can be stored in different ways: in columns, documents, graphs, or as a key-value store. 

This flexibility allows the following:

• You can create documents without defining their structure in advance;
• Each document can have its own unique structure;
• The syntax may differ in different databases;
• You can add new fields in the process of work.

SQL uses a universal structured query language to define and manipulate data. This imposes certain restrictions: before starting processing, the data must be placed inside tables and described.

Scalability

In most cases, SQL databases can be scaled vertically, which means that it is possible to increase the load on each individual server, increasing the power of the CPU, RAM, and disk. But NoSQL databases can be scaled horizontally. It means that the load is distributed by splitting data or adding more servers. One is like adding more floors to a building, and the other’s like adding more buildings to a neighbourhood. The latter allows the system to become larger and more powerful. That is why NoSQL is usually chosen for large or frequently changing databases.

Structure and Data Type

Relational databases store structured data, which usually represents objects in the real world. For example, it can be information about a person or about the contents of a shopping cart. That data is grouped in tables, the format of which has been set during the store’s design stage.

Non-relational databases are structured differently. For example, document-oriented databases store information in the form of hierarchical data structures. Here we can have objects with an arbitrary set of attributes. What would be split into several interconnected tables in a relational database can be stored in a non-relational database as a single integral entity.

Requests

Regardless of the license, RDBMS use SQL standards, so you can get data from them using the SQL language.

NoSQL databases do not use a common query format, so each NoSQL solution uses its own query system.

Support

Relational DBMSs have a long history behind them. They are very popular and offer both free and paid solutions. It’s much easier to find the answer to a relational system problem than to a problem with a NoSQL system, especially if the solution is complex in its nature.

SQL and NoSQL Databases Comparison

Best Database For Node

SQL Databases for Node.js – Comparison

General

MySQL

MySQL is one of the most widely used database management systems today. This system is used to work with fairly large amounts of information. However, MySQL is ideal for both small and large projects. An important characteristic of the system is that it is free of charge.

PostgreSQL

PostgreSQL is a popular free object-relational database management system. PostgreSQL is based on the SQL language and supports numerous features.

SQLite

The database is easily embeddable into applications. Since this system is based on files, it provides a fairly wide range of tools for working with it, compared to network DBMS. When working with this DBMS, requests are made directly to files (where data is stored), instead of ports and sockets in the network DBMS. SQLite is also very fast and powerful thanks to the serving library technologies.

Data Types

MySQL

MySQL supports the following data types:

• TINYINT: very small whole integer;
• SMALLINT: small whole integer;
• MEDIUMINT: medium-sized whole integer;
• INT: normal-sized whole integer;
• BIGINT: a large whole integer;
• FLOAT: single-precision signed floating-point number;
• DOUBLE, DOUBLE PRECISION, REAL: signed double-precision floating-point number;
• DECIMAL, NUMERIC: signed floating-point number;
• DATE: date;
• DATETIME: a combination of date and time;
• TIMESTAMP: stamp of time;
• TIME: time;
• YEAR: a year in YY or YYYY format;
• CHAR: a fixed-size string, right-padded with spaces to the maximum length;
• VARCHAR: variable length string;
• TINYBLOB, TINYTEXT: binary or text data with a maximum length of 255 characters;
• BLOB, TEXT: binary or text data with a maximum length of 65535 characters;
• MEDIUMBLOB, MEDIUMTEXT: text or binary data;
• LONGBLOB, LONGTEXT: text or binary maximum data of 4294967295 characters;
• ENUM: enumeration;
• SET: sets.

PostgreSQL

The supported field types in Postgresql are quite different, but they allow you to write the exact same data:

• bigint: signed 8-byte integer;
• bigserial: an automatically growing 8-byte integer;
• bit: fixed-length binary string;
• bit varying: a binary string of varying length;
• boolean: flag;
• box: a rectangle on a plane;
• byte: binary data;
• character varying: a fixed-length symbol string;
• character: a symbol string of varying length;
• cidr: IPv4 or IPv6 network address;
• circle: a circle on a plane;
• date: date in the calendar;
• double precision: floating-point number of double precision;
• inet: Internet IPv4 or IPv6 address;
• integer: signed 4-byte integer;
• interval: time interval;
• line: an infinite straight line on a plane;
• lseg: line segment;
• macaddr: MAC address;
• money: monetary value;
• path: geometric path on the plane;
• point: geometric point on a plane;
• polygon: a polygon on a plane;
• real: single-precision floating-point number;
• smallint: two-byte integer;
• serial: automatically incremented four-bit integer;
• text: variable length pattern string;
• time: time of day;
• timestamp: date and time;
• tsquery: text search query;
• tsvector: text search document;
• uuid: unique identifier;
• xml: XML data.

SQLite

Storage classes:

• NULL – The value is a NULL value;
• INTEGER – The value is a signed integer stored in 1, 2, 3, 4, 6, or 8 bytes, depending on the magnitude of the value;
• REAL – The value is a floating-point value that is stored as an 8-byte IEEE floating-point number;
• TEXT – The value is a text string stored using the database encoding (UTF-8, UTF-16BE, or UTF-16LE);
• BLOB – A value is a block of data that is stored exactly as it was entered.

Merge type:

• TEXT – This column stores all data using the storage classes NULL, TEXT, or BLOB;
• NUMERIC – This column can contain values ​​using all five storage classes;
• INTEGER – Functions the same as a column with a NUMERIC affinity, with an exception in the CAST expression;
• REAL – Behaves like a column with a NUMERIC affinity, except that it casts integer values ​​to floating-point representation;
• NONE – A column with an affinity of NONE doesn’t favour one storage class over another, and no attempt is made to force data from one storage class to another.

Data Storage Features

MySQL

MySQL is a relational database where various engines are used to store data in tables. However, the process of working with engines is hidden in the system itself. The engine affects neither the syntax of requests nor their execution. The main supported engines are MyISAM, InnoDB, MEMORY, and Berkeley DB. They differ from each other in how data is written to disk, as well as in their getter methods.

PostgreSQL

PostgreSQL is an object-relational database that runs on only one engine – a storage engine. All tables are represented as objects and can be inherited; all actions with tables are performed using objectively oriented functions. All data is stored on disk, in specially sorted files, but the structure of these files and the records in them vary greatly.

SQLite

SQLite is an embedded database. The word “embedded” means that SQLite does not use the client-server paradigm. In other words, the SQLite engine is not a separately working process the program interacts with, but a library the program is linked with, – the engine becomes an integral part of the program. Thus, the function calls (API) of the SQLite library are used as an exchange protocol. This approach reduces overhead, lowers response time, and simplifies the program. SQLite stores the entire database (including definitions, tables, indices, and data) in a single standard file on the computer the program is running on.

SQL Standard Support

MySQL

MySQL doesn’t support all the new features of the SQL standard. The developers chose this path of development to keep MySQL easy to use. The company does try to meet the standards, but not at the expense of simplicity. If a feature can improve usability, then developers can implement it as an extension regardless of the standard.

PostgreSQL

PostgreSQL is an open-source project. It is developed by a team of enthusiasts, and the developers try to comply with the SQL standard as much as possible, while implementing all the newest standards. But all this leads to the loss of simplicity. PostgreSQL is very complex, and because of this, it is not as popular as MySQL.

SQLite

SQLite strives to live by the “minimal but complete” principle. It does not support some complex features, but its functionality corresponds to SQL 92 in many aspects. And it introduces some of its own features, which are very convenient, albeit non-standard.

The following features are not supported:

• RIGHT and FULL OUTER JOIN. Only LEFT OUTER JOIN is implemented;
• ALTER TABLE is partially implemented. Only RENAME TABLE and ADD COLUMN are available;
• Partial trigger support. Only FOR EACH ROW triggers are available;
• Recording in VIEWS. In SQLite, VIEWS are read-only. Partially bypassed through triggers;
• Due to the implementation of the database as a single file and the departure from the client-server concept, the GRANT and REVOKE capabilities are not used;
• External keys are disabled by default. This is for backward compatibility.

Performance

MySQL

In most cases,  an InnoDB table is used to organize work with a database in MySQL. This table is a B-tree with indices. Indices allow you to get data out of the disk very quickly, meaning fewer disk operations. But scanning a tree requires finding two indices, which is already slow.

PostgreSQL

All PostgreSQL table header information is in RAM. You cannot create a table that is outside the memory. The table records are sorted by index, so you can retrieve them very quickly. For more convenience, you can apply multiple indices to the same table.

In general, PostgreSQL is faster, with the exception of operations involving the use of primary keys.

SQLite

As in MySQL, indices in SQLite are built on the basis of the B-tree algorithm. What makes it unique is that SQLite is perfectly suitable for small databases. As the database grows, the memory requirements also increase when using SQLite. There is little to no optimization for SQLite performance.

To improve the performance of the database with indices, it’s better to avoid: 

• using them on small tables; 
• using them on tables with frequent, large batch updates or inserts;
• using them for columns with a big amount of NULL values.