SQL and NoSQL

When selecting a modern database, one of the most important decisions is whether to use a Structured Query Language (SQL) or Not Only Structured Query Language (NoSQL). Both systems have unique advantages and cater to different needs, so choosing the appropriate one is key to optimal data management.

What is SQL?

SQL is a domain-specific programming language designed for managing and manipulating data within databases. It inserts, updates, queries, deletes data, creates and modifies database schemas, and defines access controls.

A SQL database is a relational database, and SQL is the main language used to create and manage the database. SQL APIs allow developers to execute database operations efficiently without repeatedly writing SQL commands.

Structured data is organized in a consistent format, often as alphanumeric characters. Financial transactions and inventory records are usually stored in SQL-based relational databases.

Examples of SQL include Db2, MySQL, Oracle Databse, Azure SQL Database

How SQL Works

SQL databases typically scale vertically by upgrading to a server with robust resources. Though less common, they can also scale horizontally through sharding or partitioning, but this is not widely supported. These databases organize data in tables with rows (records) and columns (attributes). Thanks to their strict schema, data must be organized and structured before it is used.

ACID, the acronym for the four following properties, is a requirement of SQL databases:

  • Atomicity: Transactions must fully succeed or fail, with no partial completion.
  • Consistency: Data must remain valid and follow rules at each step.
  • Isolation: Simultaneous transactions cannot interfere with each other.
  • Durability: Completed transactions are permanent, even after a system failure.

What is NoSQL?

NoSQL is a database management approach designed to handle unstructured and semi-structured data that traditional SQL databases cannot effectively process. It allows data to be ingested in its native format and supports non-relational, non-tabular data models while enabling SQL-like queries.

Unstructured data doesn’t have a predefined data model or consistent organization. Unlike structured data, which changes less often, unstructured data—like social media posts, images, audio files, and videos—is updated regularly.

NoSQL databases use a flexible schema and non-tabular data storage, allowing unstructured and semi-structured data to be stored in its native format (txt, JPG, MP3). This flexibility allows NoSQL databases to store different data structures within the same collection, unlike SQL databases that require data to conform to a predefined format.

Examples of NoSQL include Hbase, Neo4j, MongoDB, Redis

How NoSQL Works

NoSQL databases handle various data structures within the same database. With a flexible schema, they allow for easier modifications and less need to pre-organize data. You can add new fields and use different syntax across databases.

These databases excel at horizontal scaling, meaning users can add more servers or nodes to handle increased loads. They are not relational, so they don’t rely on tables and rows. Instead, they use one of four main structures:

  • Column-oriented: Data is stored in columns rather than rows.
  • Key-value stores: Data is stored as key-value pairs, like a dictionary.
  • Document stores: Data is stored in documents using formats like JSON, XML, or BSON, allowing for different types within the same database.
  • Graph databases: Data is stored as nodes and edges, showing relationships between data sets.

NoSQL follows the CAP theorem, which dictates that distributed systems can only guarantee two of the following three properties at once:

  • Consistency: Each request gets the latest data or an error.
  • Availability: Every request gets a response without errors.
  • Partition tolerance: The system continues to operate despite delays or losses between nodes.

Some NoSQL databases also support ACID properties.

NoSQL has smaller user communities compared to SQL but benefits from open-source systems, unlike many proprietary SQL languages.

NoSQL vs. SQL

Users often prefer NoSQL databases over SQL databases because they offer more flexibility and scalability. The most compelling benefit of a NoSQL system is that it enables developers to store and access data quickly and easily without the overhead associated with a traditional relational database. This means development teams can focus on delivering features faster without worrying about implementing underlying data storage.

Choosing which type of database to use largely depends on a project’s specific needs. For instance, a NoSQL system may be the better choice if a fast, scalable, and reliable database for web applications is required.  Alternatively, if the application relies on complex data queries and transactional support, an SQL system would be more appropriate.

Ultimately, there is no one-size-fits-all solution—it all comes down to what is needed from the database and which type of system can provide that most efficiently. It’s best to research both options thoroughly before making any decisions. Understanding each database’s unique features will help determine which is suitable for the business.

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SQL and NoSQL
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