If you are working on a website or online information system, chances are you are going to deal with a database and database management system (DBMS). A database refers to an organized data collection. A database management system (DBMS) is a software application that allows the user, database, and other applications to interact to each other. Thanks to them, we are able to organize all of our data, schemas, tables, queries, and various other objects in an effective and efficient way. However, there are various types of databases in the world. For a beginner, those choices can be overwhelming and confusing. Two types of databases that are currently very popular are NoSQL and MySQL. So, what is actually the difference between NoSQL and MySQL? Is one of them better than the other? Well, let’s get to know more about these two types of databases below.
What is NoSQL?
As a matter of fact, NoSQL databases have existed since as early as the 1960s. However, they were not called “NoSQL” until the early 21st century, when a surge of popularity was triggered by the needs of Web 2.0 of many large companies such as Google, Facebook, and Amazon. Nowadays, NoSQL databases are increasingly implemented in various big data and real-time web applications. NoSQL is sometimes called “Not Only SQL” to punctuate that it may support some SQL-like query languages in addition to its own.
A NoSQL database provides a mechanism for data storage and retrieval in ways other than the tabular relations of relational databases. The data structures are different from the ones used in relational databases, such as key-value, wide column, graph, and document. You can categorize NoSQL databases based on these data structures. Below are some examples of NoSQL databases:
– Key-Value: Coherence, Aerospike, ArangoDB, MemcacheDB, LMDB
– Wide Column: BigTable, Druid, Cassandra, Hypertable, HBase
– Graph: AllegroGraph, InfiniteGraph, Apache Giraph, OrientDB, MarkLogic
– Document: Apache CouchDB, DocumentDB, MongoDB, IBM Domino, HyperDex
The particular suitability of a NoSQL database depends on the problem at hand. NoSQL tends to compromise consistency in favor of availability, speed, and partition tolerance.
What is MySQL?
MySQL is an open-source relational database management system. It is perhaps the most well-known of relational databases. It was released for the first time in 1995. The name “MySQL” is actually the combination of “My”, the name of the co-founder Michael Widenius’ daughter, and “SQL”, which stands for Structured Query Language. MySQL was owned and sponsored by a Swedish company, MySQL AB, which is now owned by Oracle Corporation. MySQL is a central part of the LAMP and other AMP web application software stacks. It is extensively used in various applications. Many high-profile, large-scale websites also use MySQL, including Facebook, YouTube, Twitter, and Google (not for searches, though).
Dispelling the Myths
Before we go any further, let’s clear some myths that surround NoSQL and MySQL.
Myth 1: NoSQL / MySQL is the superior product
Are cars better than boats because they are a newer technology? Any person who answered yes should try driving a car to cross the sea. NoSQL and MySQL are there for the same thing: store data. NoSQL and MySQL uses different approaches, though, which may help or hinder your project. Despite the recent surge of popularity, NoSQL is not always better than MySQL – it is simply an alternative. Some projects are more suited to NoSQL, whereas some others are more suited to MySQL.
Myth 2: There are clear distinctions between NoSQL and MySQL
This is not always true. You see, NoSQL databases have been adopting some MySQL features and vice versa. Apparently, the separating lines will become increasingly blurred, and there will be hybrid databases with interesting features in the future.
Myth 3: The language / framework strictly determines the database
We have grown accustomed to technology stacks, such as LAMP (Linux, Apache, MySQL, PHP), MEAN (MongoDB, Express, Angular, Node.js), and Java-Apache-Oracle. There are historical, practical, and commercial reasons to using these stacks, but they are not the absolute law. You can use MongoDB, which is a NoSQL database, in your PHP project. You can connect to MySQL in Node.js. The database is determined by your requirements, not the language / framework. Well, that said, there is no need to make your life purposely difficult; while an unusual combination or a mix of MySQL and NoSQL databases is possible, there will be significantly fewer tutorials and resources and it will be tougher to find support. So, there is no need to go for an anti-mainstream approach unless that is necessary.
NoSQL vs. MySQL
Now, let’s see the primary differences between NoSQL and MySQL.
1. Table vs. Collection
A MySQL database stores data in related data tables. A database consists of one or more tables, and each table has rows (records) and columns (fields). Every row is a different data record. MySQL has a rigid design; you cannot use the same table to store different information or insert a string in an integer field. Due to the strict rigidity, MySQL makes it very difficult to make mistakes.
On the other hand, a NoSQL database stores data in JSON-like field-value documents. Similar documents are grouped into a collection, which is analogous to MySQL’s table. However, a NoSQL database will not complain if you store different data in a document. For example, document A only has two fields, which are ‘productname’ and ‘price’, but document B can have three fields, which are ‘productname’, ‘price’, and ‘review’). Thus, NoSQL is much more flexible and forgiving, but it can lead to consistency issues.
2. Schema vs. Schema-less
In MySQL, it is impossible to add data before you define the tables and fields – the schema. The schema needs to be designed and implemented in order to store and manipulate data. You can make changes later to the schema, but large changes can be complicated. On the other hand, NoSQL allows you to add data anywhere, anytime. There is no need to specify a design up-front.
3. Normalization vs. Denormalization
MySQL hates data redundancy (storing the same data in multiple places). In order to reduce or eliminate data redundancy, we perform normalization. Normalization offers practical benefits; it prevents you from entering the same data over and over again, updating just a single record to change a wider range of information, and reducing the chance of making a mistake.
NoSQL also allows you to perform normalization, but it is not always practical. In NoSQL, you may want to denormalize your documents for faster queries – but, of course, updating multiple records will be so much slower.
4. To JOIN or not
People who have been used to MySQL may be shocked upon finding out that NoSQL has no way to obtain data from multiple tables using just a single query statement. In MySQL, there is the beloved JOIN clause to do the task. In NoSQL, you will have to fetch all documents and manually link the needed documents in the program code. That’s why denormalization is essential in NoSQL; it allows you to retrieve all data of a specific item with just a single request.
5. Syntax and Transaction
In MySQL, you can execute two or more updates in a transaction, which is a wrapper that guarantees all of the contained updates are either success or failure. MySQL uses a lightweight declarative language that is incredibly powerful and efficient and has become an international standard.
6. Performance, Scaling, and Practicalities
The three aspects compared here are subjective matters. MySQL is considered slower than NoSQL because of the JOINs and complex queries. NoSQL’s denormalization allows you to take everything more quickly. But, for updating records, MySQL is more effective and efficient than NoSQL because it is faster and ensures integrity.
As the data grows, you may find the necessity to distribute them to multiple servers. Scaling can be tricky for MySQL. The simplest option is perhaps clustering, making multiple servers access the same center. NoSQL’s flexible data structure makes scaling easier. Some NoSQL databases even have built-in scaling functions.
|- Uses collections and documents with fields and values||- Uses tables with fields and records|
|- Flexible data structure||- Rigid data structure|
|- Does not need a schema prior to data||- Requires a schema prior to data|
|- Denormalization is usually preferred||- Normalization is usually preferred|
|- Relatively more complex syntax, without JOINs and Transactions||- Relatively simpler syntax, with JOINs and Transactions|
|- Suitable for projects with indeterminate/evolving data, looseobjectives, and prioritization on speed and scalability||- Suitable for projects where data integrity and consistency are imperative and where a standards-based technology is preferred|
NoSQL and MySQL are doing the same thing in different ways. Despite the recent surge of popularity, NoSQL is not always better than MySQL. They are different alternatives for different cases. NoSQL is better suited for projects that have indeterminate or evolving data, looser objectives, and prioritization on speed and scalability. Meanwhile, MySQL is better suited for projects where data integrity and consistency are crucial, as well as projects with static data structures and where a standards-based technology with decent support is needed.