A brief discussion of database knowledge starting with MongoDB

This article brings you a brief discussion of database knowledge starting from MongoDB. It has certain reference value. Friends in need can refer to it. I hope it will be helpful to you.

Today’s topic is to talk about databases from MongoDB. In daily projects, we generally use mysql as the database, but once there is a problem, we often hear something like "How about replacing it with "Try MongoDB" sounds, so let us newbies come and talk about databases

What is a database

Let's put it in the simplest terms, a database is a place that saves data. Warehouse

The basic concept of database (Database)

• A database is a warehouse that organizes, stores and manages data according to a certain data structure

• The programs we write all run in memory. Once the program ends or the computer breaks, all the data in the program will be lost; so we need to persist some program data to the keyboard. , to ensure data security.

• Database is a common choice for large-volume data persistence, 1. File 2. Database

Why use database to store data

• The database is structured

• The database can provide various interfaces to make data processing (addition, deletion, modification, and query) quick and convenient

• Various languages ​​​​(PHP, jsp, .net..) provide complete interfaces

Database popularity (source: https://db-engines.com /en/ranking)

It can be seen from the statistical data that the most popular DBMS is "relational", among the top five Occupying four places, the data has been expanded to the top ten, and relational databases also account for seven places.

Why do most programmers prefer to use MySQL?

• Open source, only enterprises need to purchase a license

• Widely used: can be widely used on most platforms, such as Linux, Windows , Ubuntu, Mac OS

  ##Suitable for PHP (PHP is the best in the world), and can also be used with other programming languages, such as JAVA, PERL, C, C, etc.

• Suitable for small and large Application

• So why is MongoDB still included in the top five if relational databases are so good? Let’s take a look at
• What are the shortcomings of relational databases and MySQL? ?

• Scalability: Adding more data to a specific record may involve scaling to multiple tables, columns, and rows, and because the data is stored row by row, even if it is only done for one of the columns Operation, the relational database will also read the entire row of data from the storage device into the memory, resulting in higher I/O.

A defect arising from the first item is that it cannot be stored Data structure

Speed: Due to the problem of data structure, it takes a certain amount of time to analyze the data. In addition, only substring matching queries can be performed. When the data in the table gradually becomes larger, , the matching of like queries will be very slow, even if there is an index.

• Before using it, you need to write a schema to define the table. At the same time, the table structure schema is inconvenient to expand if needed. Modifying the table structure requires executing DDL (data definition language) and statement modification. During the modification, the table will be locked.

• What makes MongoDB so attractive?

• Flexibility: The document structure is more consistent with the way developers code in their respective programming languages, which are clear and structured in key-value pairs so that they can be easily added at any time and edit data/documents

• Supports various queries: fields, expressions, range queries, JavaScript functions, etc.

Faster turnaround time : Because related data stored in multiple tables in a MySQL database is stored in the same document in MongoDB

• There is no strict schema: the document can be created before defining the document structure

• MongoDB’s features make it more suitable for processing large amounts of data
Let us first compare the two and then explain in detail

• ##Version1995- 2018 (mysql 8.0)2009 StructureRelationalNon-relationalFlexibilityWeak, database schema needs to be defined before use Considerable flexibility compared to MySQL - Define unnecessary schema ScalabilityIt is possible, but it is more difficult. MySQL database can be expanded vertically and more resources can be added to a single serverMore efficient than MySQL Scalable. MongoDB is horizontally scalable and more servers can be added to grow your database Requires DB AdministratorYesNo - Developers and Administration Accounting firms and banks, as well as other companies that require structured data with a clear schema. Ideal for businesses with more or less fixed requirements (with the exception of twitter) with real-time data, IoT, content management, mobile apps, social networks, big data/network analytics oriented systems and systems that do not require clear Ideal for businesses whose schema or structured data is constantly changing

  Flexibility

  First of all, let’s talk about flexibility. For example, there will be many products in a mall, and these products all have their own unique attributes, such as TV screen size and screen resolution. efficiency, and air conditioners have attributes such as cooling type and outdoor unit noise. It is very difficult to put them into the product table, which adds extra work for programmers to design data tables, and MongoDB does not have Schema (schema, data model). It will seem very simple.

  MongoDB’s flexibility is also reflected in unstructured and semi-structured data. MongoDB provides full-text indexing and also supports geolocation query and indexing. For example, a user wants to know where there are public restrooms within a five-kilometer radius. This is a "geographic range query." Then he searches for the nearest bike. Mobike uses MongoDB to complete such "distance sorting query".

  Scalability

  The data cannot be placed on one machine, so sharding is needed to put it on several machines. Sharding has been a native feature of MongoDB for many years and is efficiently integrated with other MongoDB features.

  For example, a complex aggregation query in a sharded cluster will be automatically allocated to multiple nodes for running based on the Shard Key (shard key), and the computing tasks will be pushed down to the data nodes as much as possible. Finally, Aggregate the results of all nodes on one node. Sharding can also automatically migrate data between nodes to balance their data volume. At the same time, combined with MongoDB's replication (replica set) technology, data loss can be effectively avoided (during testing, it was found that mongo will automatically discover all machine addresses of the replica set. When a Mongo is stopped, the connected server will not Error report)

  Using sharded cluster structure distribution in MongoDB:

  

  Disadvantages of MongoDB

  • As we all know, MongoDB takes up a lot of server memory

  • MongoDB is slightly less secure

  • too free and flexible files Data errors caused by storage format (...)

  • The size of a single document is limited to 16 M

  • For array types Data operations are not rich enough

  When to choose MongoDB

  After saying so much shit, the most important thing is when do we choose to use MongoDB

  • Log system, the log information generated during the operation of the system generally has many types, a large scope, and the content is relatively messy. These messy logs can be collected and managed through MongoDB

  • Geographical location storage. MongoDB supports geographical location, two-dimensional spatial index, and can store longitude and latitude, so two points can be quickly calculated. The distance between them, and other location information

  • The data scale is growing rapidly (such as the supplied attention information)

  • Need to ensure a highly available environment

  • File storage requirements

  • Other scenarios, such as game development, user information, equipment, points, etc. can be stored through MongoDB. In addition Logistics systems, social systems, and even Internet of Things systems

  Types of databases

  Having said so much, why do we put mysql and MongoDB together to compare and choose? It is because they are different types of databases. From the development of databases to the present, they are roughly divided into three types

  RDBMS (relational database)

  The first thing to mention must be the one we are most familiar with. The relational database to which mysql database belongs.

  Features of relational databases:

  • For example, MySql, sql server Oracle, etc.

  • Features are represented through tables Establish association

  • basically use SQL language to manage the database

  Nosql (non-relational database)

  NoSql, also It is the database type of MongoDB, originating from a Meetup held in San Francisco in 2009, where a description of NoSql technology appeared: open source, distributed, non relational databases

  Characteristics of non-relational databases:

  • There is no concept of rows and columns and the json class is used to store data

  • A collection is equivalent to "Table", document is equivalent to "row"

  • Friction between normalization and non-standardization.

  • Standardization limits innovation, non-standard words cannot be unified

  NoSql was interpreted as Non-Relational when it was first proposed, and there is also No-sql means, but with the rapid development in recent years, SQL has gradually been used in a wider range of fields. Therefore, SQL is no longer an exclusive feature of RDBMS. SQL capabilities have also been introduced in the NoSql technology system, thus evolving The concept of Not-Only-SQL came out

  Most NoSql technologies weaken the support for ACID semantics and complex related queries, adopt a simpler or more professional data model, and optimize the read and write paths, thus Can be exchanged for higher read and write performance

  NewSql

  According to the definition in the wiki

  NewSQL is a class of modern relational database management systems that seek to provide the same scalable performance of NoSQL systems for online transaction processing ( OLTP) read-write workloads while still maintaining the ACID guarantees of a traditional database system.

  NewSql can be said to be the product of the combination of traditional RDBMS and NoSql technology. Therefore, the typical NewSql technology can be understood as distributed It is a basic prerequisite for a relational database to support distributed transactions. NoSQL and NewSQL have a lot of overlap in their technology stacks, but there are obvious differences in whether they support relational models and how well they support complex transactions. Since I don’t know much about it, I won’t say much here.

  Here I will simply introduce the types of databases. A storage technology that belongs to NoSql, NewSql, or RDBMS cannot be simply classified. After all, technology is constantly improving. For example, MySQL is now also Compatible with nosql features:

  

  Some people may wonder why transactions are not mentioned when introducing the shortcomings of MongoDB. This is because in In the MongoDB 4.0 version in the summer of 2018, MongoDB introduced transaction functions and supported multi-document ACID features, such as using the mongo shell for transaction operations

  

  Specific stress test data will be added later

  	MySQL	MongoDB

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