Difference between SQL and NoSQL, What is SQL Database?, What is NoSQL Database?, How SQL works?, How NoSQL works?, and When to use SQL vs NoSQL.
Difference between SQL and NoSQL
There are a lot of databases used today in the industry. Some are SQL databases, some are NoSQL databases.
The conventional database is SQL database system that uses tabular relational model to represent data and their relationship.
The NoSQL database is the newer one database that provides a mechanism for storage and retrieval of data other than tabular relations model used in relational databases.
- What is a SQL database?
- What is a NoSQL database?
- How SQL works?
- How NoSQL works?
- When to use SQL?
- When to use NoSQL?
1. What is a SQL database?
SQL database or relational database is a collection of highly structured tables, wherein each row reflects a data entity, and every column defines a specific information field.
Relational databases are built using the structured query language (SQL) to create, store, update, and retrieve data. Therefore, SQL is the underlying programming language for all relational database management systems (RDBMS) such as MySQL, Oracle, MS SQL Server, IBM DB2, and PostgreSQL, among others.
SQL database tables
SQL database server stores and organizes data in tables. In RDBMS, tables are fundamental database objects logically designed to collect data in rows and columns format.
Columns: Each column holds specific attribute information, and column properties define the data type (for example, numeric or textual data) and range it can accept.
Rows: Database users can add data to each row and execute SQL queries to retrieve data. For the primary key, each row holds a unique value which also helps overcome data duplication challenges.
2. What is a NoSQL database?
NoSQL databases are not relational, so they don’t solely store data in rows and tables. Instead, they generally fall into one of four types of structures:
Column-oriented, where data is stored in cells grouped in a virtually unlimited number of columns rather than rows.
Key-value stores, which use an associative array (also known as a dictionary or map) as their data model. This model represents data as a collection of key-value pairs.
Graph databases, which represent data on a graph that shows how different sets of data relate to each other. Neo4j, RedisGraph (a graph module built into Redis) and OrientDB are examples of graph databases.
Examples of NoSQL databases
MongoDB, Redis, FaunaDB, CouchDB, Cassandra, Elasticsearch, Neo4j, and HBase.
3. How SQL works?
In general, SQL databases can scale vertically, meaning you can increase the load on a server by migrating to a larger server that adds more CPU, RAM or SSD capability.
SQL database schema organizes data in relational, tabular ways, using tables with columns or attributes and rows of records.
RDBMS, which use SQL, must exhibit four properties, known by the acronym ACID. These ensure that transactions are processed successfully and that the SQL database has a high level of reliability:
Atomicity: All transactions must succeed or fail completely and cannot be left partially complete, even in the case of system failure.
Consistency: The database must follow rules that validate and prevent corruption at every step.
Isolation: Concurrent transactions cannot affect each other.
Durability: Transactions are final, and even system failure cannot “roll back” a complete transaction.
Because SQL databases have a long history now, they have huge communities, and many examples of their stable codebases online. There are many experts available to support SQL and programming relational data.
4. How NoSQL works?
Unlike SQL, NoSQL systems allow you to work with different data structures within a database. Because they allow a dynamic schema for unstructured data, there’s less need to pre-plan and pre-organize data, and it’s easier to make modifications. NoSQL databases allow you to add new attributes and fields, as well as use varied syntax across databases.
5. When to use SQL?
Regarding the first aspect, SQL databases are a more suitable option than NoSQL when data integrity and consistency is key within an organization.
There is often the misconception that relational databases are not a good option to handle large amounts of data. That is not exactly true. Many SQL databases, such as Oracle, PostgreSQL and MySQL, can indeed handle very respectful amounts of data.
6. When to use NoSQL
NoSQL databases are able to store various types of data and do not need to be as structured as SQL databases. Hence non-relational databases allow for great adaptability and flexibility, making it a more suitable choice when handling large sets of unstructured and unrelated data.