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This article mainly explains "what are the advantages of NoSQL database". Interested friends may wish to have a look at it. The method introduced in this paper is simple, fast and practical. Let's let the editor take you to learn "what are the advantages of NoSQL database"?

1. Brief introduction

SQL:

SQL is an abbreviation for structured query language. IT engineers have been searching for information quickly in large relational databases (DBMS) for a long time.

SQL is widely used today because it is one of the most structured and fastest database organization and query devices; different names represent different improved versions, such as Oracle's MySQL and Microsoft's SQL Server. In addition, SQL has a predefined structure and pattern, which is the most recommended choice for many companies.

NoSQL:

The acronym "NoSQL" has two different interpretations, but it is not yet clear:

For some people, it is "No SQL", that is, a different query language than SQL is used.

For others, it is not just "SQL", that is, a combination of SQL and other information retrieval tools.

This term is related not only to technical characteristics, but also to the historic generation of DBMS that emerged in the 1910's. The main reason for NoSQL's invention is that it solves the problem that the same database on one website can be used by millions of users around the world at the same time; a typical problem exists in companies like Amazon.

The author tries to reduce the complexity of query language and simplify the architecture of database through NoSQL. These databases include column-oriented, document-oriented, graphics-oriented, and key / value-oriented data. NoSQL consists of a variety of products, each with a unique set of features.

Main differences:

SQL databases have a predefined schema, while NoSQL databases have a dynamic schema for unstructured data.

SQL databases are vertically scalable, while NoSQL databases are horizontally scalable. SQL databases are extended by adding hardware capabilities such as CPU, RAM, or SSD.

NoSQL databases reduce the load by increasing the number of data servers. It's like adding more floors to the same building, rather than adding more buildings in the neighborhood.

SQL databases use SQL (structured query language) to define and manipulate data, which is very powerful. In NoSQL databases, queries focus on document collection. Sometimes called UnQL (unstructured query language). The syntax for using UnQL varies greatly between different NoSQL databases.

SQL database is a table-based database, while NoSQL database is a database based on key-value pairs. This means that the SQL database represents data in the form of a table, which consists of a certain number of rows that represent the data, while the NoSQL database is a collection of key-value pairs, documents, graphic databases, and so on.

two。 Historical factors

(1) the historical dominance of relational DBMS.

Relational DBMS created in the 1970s has gradually become the mainstream, and has become a very common mainstream database paradigm in the early 1990s.

In the 1990s, salespeople in many logistics companies began to use it to store business data. In fact, they have neither a mouse nor a user interface to search for some information stored on the server, which is usually connected by professional lines and is far apart, they are used to enter SQL commands through the keyboard and can retrieve information about the availability of specific products or raw materials in seconds.

There are several other database models, such as object-oriented database management system, hierarchical database management system, object-relational database management system, but their use is very limited.

Since the beginning of this century, with the development of large Internet companies such as Google and Amazon, a large number of unstructured data have emerged, and its growth rate is far faster than that of structured data that no longer conforms to the RDBMS relationship model. Cluster computing has also been developed, and the dominant position of relational model has been questioned because of its limitations in new practice.

(2) the pioneer of NoSQL model

Large web companies have to deal with very large amounts of data, which is why they face the inherent limitations of traditional relational DBMS in the first place.

These systems strictly apply ACID attributes (atomicity, consistency, isolation, persistence) and are usually designed to run on a single computer, and scalability problems quickly arise. To meet these limitations, some companies have begun to develop their own database management systems that can run on distributed hardware architectures and handle large amounts of data:

Google (BigTable)

Amazon (DynamoDB)

LinkedIn (Voldemort)

Facebook (Cassandra and HBase)

Baidu Hypertable)

Maintaining good performance by simply increasing the number of servers is a reasonable solution to reduce costs, especially if revenue increases as activity grows.

3. Popular database

In order to choose the right management system, it is important to understand what exists in the market. Take a look at the following five popular SQL and NoSQL databases, both paid and free.

(1) SQL database products:

MySql: it's free, and even the free database engine provides a lot of functionality.

Postgres: this database management engine is extensible, can handle tb-level data, and has a variety of predefined functions.

The Oracle:Oracle database management tool is a powerful combination of the latest ideas and features.

SQL Server: very fast and stable, and works well with other Microsoft products.

The SQLite:SQLite database is very smart and can be set up quickly, and it can also be used to store data in the actual database of smartphone applications (iPhone or Android).

(2) NoSQL database products:

MongoDB:MongoDB is a flexible / reliable database that attracts readers to the world of NoSQL. Management and maintenance is very simple and fast.

Hbase: it is a column-oriented database that helps improve query performance and collections.

The linear scalability provided by Cassandra:Cassandra allows you to easily expand / shrink clusters by simply adding / removing servers.

Redis: very simple and straightforward to use. Download Redis and start using it in the next five minutes.

CouchDb: because CouchDB can store serialized (JSON format) unstructured data and Restful HTTP API, it is ideal for Web and mobile applications.

4. NoSQL database design

The main feature of NoSQLDBMS is to support the operation of large amounts of data and horizontal scalability. At present, however, the difficulty faced by most companies is how to solve the problem with the most appropriate technology and make the application respond.

To solve this problem, you must first have a good understanding of different types of NoSQL databases.

There is a common misconception that all NoSQL databases are created equally. In fact, these databases can be divided into four categories: document-oriented databases, key / value databases, column databases, and graph-oriented databases. They all have one thing in common: they support models that are more flexible and dynamic than traditional relational databases.

In fact, each category has its own properties and limitations. No database can solve all the problems. The database must be selected according to the needs of the project.

You must consider what type of data will be manipulated and how the application will eventually use it.

(1) document-oriented database: mixed structure

The document-oriented NoSQL database stores and extracts data as key / value pairs, but the value portion is stored as a document. The document is stored in JSON or XML format.

MongoDB, Apache CouchDB, MarkLogic are document-oriented databases

(2) key / value database:

Key-oriented databases have a large number of key and value hashes. It represents the simplest form of an NoSQL database. Associating unique keys with values in the data is intended to greatly improve application performance based on relatively simple datasets.

Redis, Riak, Memcached and Aerospike are examples of key-value databases.

(3) column database:

The column database saves data in a table with a large number of columns. Each storage block contains data from a single column, and each column is processed separately. They have high performance on aggregate queries such as COUNT, SUM, AVG, MAX, and so on, because the data is easily fetched from the column.

HBase, Cassandra, and Accumulo are examples of column databases.

(4) graphic-oriented database:

A graph-based database is a network database that stores data elements in a "graph" structure, which makes it possible to create associations between nodes and eventually become the basis of recommendation engines or social networks.

A lot of information can be obtained from the graphic database. For example, you can use graphics techniques to determine the relationship between different people based on their interests.

Image source: neo4j.

Neo4J, InfiniteGraph and FlockDB are examples of graphics-oriented databases.

5. 5 criteria for selecting the appropriate database type for an application

How to choose which type of database is most suitable for a project? Decisions can be made based on the following list:

Type of data to store: SQL databases are not suitable for hierarchical data storage. However, the NoSQL database is more suitable for hierarchical data storage because it follows the key-value pair method or the graph method. NoSQL databases are the first choice for large datasets.

Scalability: in most cases, SQL databases are vertically scalable. The increased load can be managed by adding processors, RAM, SSD, and so on on a single server. NoSQL databases, on the other hand, are horizontally scalable. You can simply add some additional servers to the NoSQL database infrastructure to handle heavy data flows. Therefore, the appropriate database type can be selected according to the device.

Highly transactional applications: SQL databases are more stable and guarantee atomicity and data integrity, making them more suitable for applications of intensive transaction types. Although NoSQL can be used for transactional purposes, it is still not comparable to SQL, but it can be used for complex transactional applications.

Complex queries: SQL databases are ideal for environments that require a lot of queries, while NoSQL databases are not suitable for complex queries. So the query in NoSQL is not as powerful as the SQL query language.

Attributes: SQL databases emphasize ACID attributes (atomicity, consistency, isolation, persistence), while NoSQL databases follow the Brewers CAP theorem (consistency, availability, and partition tolerance).

6. From RDBMS to NoSQL

No matter which NoSQL database design you choose, there are some serious challenges in migrating data to it. The design of the data model in NoSQL has additional complexity, and you need to know the end use of the data. It is not enough to know that the application will process billing and customer information, but you must also know how the data will be presented to the end user.

Therefore, data modeling in NoSQL databases requires real technical expertise in addition to an in-depth understanding of end-user usage.

Is it time to replace SQL with a NoSQL solution?

In the author's opinion, this is a difficult question to answer. Because in most cases, instead of replacing SQL with a NoSQL solution, you switch from one solution to another when the application and use cases show that changes are needed.

In general, the need for flexibility and scalability will drive this shift when building modern Web and mobile applications.

Many companies try to support loads in their web applications, so they choose to simply add web servers to the load balancer to support more users.

There is no doubt that scalability is a fundamental competitive advantage in the increasingly important world of cloud computing, and virtual machine instances can be easily added or removed to meet changing needs.

Relational database (RDBMS) does not allow simple extension, nor does it provide a flexible data model. Managing more users means adding larger servers, which are complex and expensive, unlike low-cost hardware, "commodity hardware" and cloud architectures.

Organizations are beginning to see performance problems with relational databases for existing or new applications. Especially with the increasing number of users, they realize that the need for faster and more flexible databases becomes very important. It's time to move to NoSQL!

What are the main steps required for the transition from SQL to NoSQL?

The application / project may vary greatly from organization to organization, so the transformation will depend on the use case. Here are some general guidelines for transition:

(1) understand the core requirements of the application

Here are some requirements that correspond to the requirements of the NoSQL database:

Expandability

Rapid application development: changing market requirements and continuous data modification

Stable performance: short response time and better user experience

Operational reliability: mismanaged high availability with minimal impact on the application, and integrated monitoring API for better maintenance

(2) understand the different types provided by NoSQL

As mentioned earlier, there are different types of NoSQL database management systems. For example, the document-oriented NoSQL database-Couchbase and MongoDB are two of the most well-known and widely used examples.

In addition, Cassandra may also be a solution, and its cylindrical model can be used for data analysis. Neo4j is a graphical database that may be a perfect database for applications that need to store relationships between entities.

(3) build a prototype.

Once you have narrowed down the possible choices of database types, you can try to develop a prototype that integrates the main features of the application. This prototype will help assess response time, throughput performance, and scalability.

(4) document modeling and development.

For document-oriented databases, take a few days to model the data from a fixed table graph to get a flexible document model.

(5) deploy and then produce

Operational stability is a very important aspect of interactive web applications. Test the deployment again and again, just like testing applications that typically use traditional RDBMS systems.

(6) keep up with the latest trend

Today, a large number of high-quality training provides practical courses on NoSQL, and the best way to ensure a successful implementation of NoSQL is to update the latest version.

Don't worry, you will easily accept some NoSQL technologies, especially if you are familiar with JSON document formats. Developers who use SQL extensively may need to adapt and learn document modeling methods. It is an important aspect to rethink how to use documents to logically construct data rather than normalizing the data into a fixed database schema.

At this point, I believe you have a deeper understanding of "what are the advantages of NoSQL database?" you might as well do it in practice. Here is the website, more related content can enter the relevant channels to inquire, follow us, continue to learn!

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