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MongoDB 是NoSQL 数据库，适合存JSON格式数据，MySQL是关系型数据库，适合存table格式数据
MongoDB扩展性更好，MySQL支持主从和cluster但是感觉不咋样
mongodb 没有事务、联表(join)查询的支持，其实有inlook 简单的联表查询支持的
mongodb 插入更新大量数据比较快，mysql 查询大量相关数据比较快
MongoDB有很好的HA和恢复支持
some important quotes:
- MongoDB is an ideal choice if you have unstructured and/or structured data with the potential for rapid growth while MYSQL is a great choice if you have structured data and need a traditional relational database.
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In general, a project with frequently updated data will benefit more from a relational database than a nonrelational one. An example of such a project would be any kind of transactional system, like an ecommerce platform, a workflow application, or a payment processor.
On the other hand, a project that rarely updates information, such as an analytics application where data doesn't change after it has been collected, will benefit more from a nonrelational database.
可以考慮使用 NoSQL (譬如 MongoDB)，如果
- 想快速啟動小專案測試 idea
- 資料格式不確定 (unstable schema)，而未來很有可能調整
- 資料之間沒有複雜的關聯、或未來讀取資料時不需要使用 JOIN 的功能
- 著重在快速讀取資料與可用性，而非 ACID
可以考慮使用 RDBMS (譬如 MySQL)，如果
- 已經有明確的資料格式，未來不會大幅的變動
- 資料之間的關聯很重要
- 想要更有效率的讀取資料，未來會大量使用到 JOIN 的功能
- 更著重在資料操作的準確性與一致性 (ACID)
上述的情境主要是在個人專案上，如果實際在業界開發，還需要考量到
- 商業邏輯的設計
- 目前使用的系統（如何加入，需不需要做調整或轉移）
- 部署方式
- 成本計算
- 維護與營運考量
- 未來的擴充性
| MongoDB | MYSQL |
|---|---|
| MongoDB represents data as JSON documents. |
MySQL represents data in tables and rows. |
| In MongoDB, you don’t need to define the schema. Instead, you just drop in documents don’t even need to have the same fields. | MySQL requires you to define your tables and columns before you can store anything, and every row in a table must have the same columns. |
| MongoDB has a pre-defined structure that can be defined and adhered to, but also, if you need different documents in a collection, it can have different structures. | MySQL uses Structured Query Language (SQL) for database access. You can’t change the schema. |
| Supported languages are C++, C | Supported languages are C++, C and JavaScript |
| Ongoing development is done by MongoDB, Inc. | Constant development is done by the Oracle Corporation. |
| MongoDB supports built-in replication, sharding, and auto-elections. | MySQL supports master-slave replication and master replication. |
| If an index is not found, every document within a collection must be scanned to select the documents which offer a match to the query statement. | If an index is not defined, then the database engine needs to scan the complete table to find all relevant rows. |
| GPL v2/ Commercial license available OD | GNU AGPL v3.0/ Commercial licenses available OD |
| If most of your services are cloud based MongoDB is the best suited for you. | If data security is your priority then MYSQL is the best option for you. |
| MongoDB places no restrictions on schema design. | MySQL requires you to define your tables and columns before you can store anything. Every row in a table must have the same columns. |
| MongoDB uses JavaScript as query language. | MySQL uses the Structured Query Language (SQL). |
| MongoDB doesn’t support JOIN. | MySQL supports JOIN operations. |
| It has the ability to handle large unstructured data | MySQL is quite slow in comparison to MongoDB while dealing with large databases. |
| Real-time analytics, content management, internet of things, mobile apps | Structured data with clear schema |
| No schema definition required so lesser risk of attack due to design | Risk of SQL injection attacks |
| An ideal choice if you have unstructured and/or structured data with the potential for rapid growth. | A great choice if you have structured data and need a traditional relational database. |
Ref：
https://www.bmc.com/blogs/mongodb-vs-mysql/#Disadvantages_of_both
https://blog.panoply.io/mongodb-and-mysql
https://www.guru99.com/mongodb-vs-mysql.html