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Micron technology glossary

NoSQL databases

NoSQL databases offer an alternative to traditional relational databases, providing expanded flexibility, scalability and usability. These non-relational database management systems are designed to store vast quantities of data in a way that is simple, accessible and efficient for large organizations.

NoSQL stands for “not only SQL,” indicating that these databases support more functionality than structured query language (SQL) only. As a result, NoSQL databases are valuable for handling complex and large-scale data requirements.

Discover what the key attributes of NoSQL databases are and how they can be used, with Micron.

What are NoSQL databases?

NoSQL database definition: NoSQL stands for “not only SQL,” meaning that these databases support more functionality than structured query language (SQL) only.

NoSQL databases are non-relational databases; that is, they store data in a way that allows for access and querying outside rigid table structures.

While​ ​relational databases work based on tabular formatting that highlights relationships between data points, NoSQL databases house data within various structures that do not require a schema.

This strategy allows the database to be scaled much more simply than relational databases. They are also more flexible to use as they offer a range of formatting and organizational options.

NoSQL databases can be developed simply, allowing greater accessibility as a technology and offering an entry point to large data storage that organizations and individuals can benefit from.

The core benefits that attract people to NoSQL databases as opposed to relational options are the high performance, scalability and functionality. These databases can be optimized for specific data models to the preference of individual database administrators. 

In conjunction with the high functionality and API compliance, NoSQL databases are highly usable in niche, individualized ways.

How do NoSQL databases work?

NoSQL database is an umbrella term covering different ways that data can be stored, so each type works slightly differently. Additionally, the flexibility of NoSQL databases means that developers can use several programming languages, allowing for personalized functionality.

Despite individual differences, NoSQL databases share some common features:

  • Individual NoSQL databases follow flexible schemas, offering a semi-structured format.
  • NoSQL databases can be scaled horizontally, meaning more computers pick up the expanded workload and users do not have to add capacity to existing servers.
  • Each database is optimized for specific data models, formatting styles and programming languages.

What is the history of NoSQL databases?

  • 1998, Strozzi NoSQL: The term NoSQL was first used with the introduction of the Strozzi NoSQL open-source relational database. This initial database was relational, so it was not yet fully distinct from SQL databases.
  • 2009, further development: Interest in NoSQL databases was renewed in the late 2000s, with an event organized to discuss open-source non-relational databases.

What are key types of NoSQL database?

There are a few key types of NoSQL database, with variations in how data is stored and accessed. This flexibility of storage solutions allows organizations to adapt their databases to suit their needs and preferences, enabling individual users to access, format and visualize data effectively.

Graph databases are one option for data storage within NoSQL databases. Their name is derived because they store, maintain and visualize data in graphs. Although NoSQL databases are non-relational, this formatting option allows relationships between data points to be visualized and compared, making it an excellent solution for relational data storage in a non-relational system.

  • Key-value databases are the simplest form of NoSQL database. They store data in pairs, where each key is unique and associated with a specific value. For example, a key-value pair could be key = name and value = Alice. This structure enables intuitive storage and retrieval of data.
  • Within document databases, semi-structured data is used for storing and querying data. Data may be stored in files, such as JSON, that are easily accessible and allow data to be updated and amended simply.
  • As you may expect, column-oriented databases store data in columns. This is a similar system to relational database tables but allows a little more flexibility. The key benefit of formatting data in columns is that it simplifies locating and retrieving data.
  • In-memory databases provide a speed-oriented solution by storing data in memory, which allows data to be accessed quickly and efficiently in real-time applications.

How are NoSQL databases used?

NoSQL offers an extremely varied and flexible approach to data storage, so there are plenty of use cases across industries. Data is becoming exponentially important to our lives and to the way that businesses operate, so storing that data in a mindful, efficient way is crucial to the successful operation of all organizations.

NoSQL databases offer a data storage solution that provides security, scalability and flexibility, which makes them usable in a wide range of ways.

One such use case is real-time analytics. Many businesses and organizations need to track how their operations, and especially online platforms, are performing. NoSQL databases allow this performance to be tracked in real time because low-latency options mean that data can be identified, stored, and accessed quickly and regularly.

NoSQL can also be extremely valuable with Internet of Things technology, as IoT devices generate and store vast quantities of diverse data. This data needs to be categorized and stored efficiently. NoSQL databases offer a scalable solution for this amount of data, especially since IoT devices can see sudden spikes in data storage requirements, which NoSQL databases can accommodate.

NoSQL databases are used in edge AI applications to manage and process data locally on edge devices. This functionality enables faster data processing and real-time decision-making, which are crucial for applications like autonomous vehicles and smart devices.

NoSQL databases are also used by major social media applications for storing and organizing the enormous amounts of data generated by social media use. Major apps have millions of users, all generating diverse kinds of data in extremely high volumes. Low-latency access and storage for this data are essential, making NoSQL databases a valuable solution.

Frequently asked questions

NoSQL databases FAQs

NoSQL is an acronym for “not only SQL.” It indicates that NoSQL databases support more functionality than structured query language (SQL)only, allowing for various data storage and querying methods.

SQL is the standard query language of relational databases. Although it is commonly pronounced “seekwəl,” the preferred pronunciation is “S-Q-L.” It is used for creating, querying and interacting with relational databases. NoSQL refers to non-relational database management systems that can operate using SQL and other languages and formats. This flexibility makes NoSQL databases extremely valuable for handling complex and large-scale data requirements.

PostgreSQL is a relational database, whereas NoSQL databases are non-relational. Relational databases store data in structured tables with predefined schemas, making them ideal for applications requiring complex queries and transactions. They are preferred when data integrity and relationships between entities are crucial, such as in financial systems and enterprise resource planning (ERP) applications. In contrast, non-relational databases store data in flexible formats, such as key-value pairs or documents, offering greater scalability and performance for handling large volumes of unstructured data. They are desirable for applications that require rapid development and scalability, such as social media platforms, big data analytics and content management systems.

Choosing between relational and non-relational databases depends on your specific data requirements and application needs. Relational databases, such as PostgreSQL, are ideal for applications requiring complex queries, transactions and data integrity. They store data in structured tables with predefined schemas, making them suitable for financial systems, ERP applications, and scenarios where relationships between data points are crucial.
 

On the other hand, non-relational databases, like NoSQL databases, are better for applications that require rapid development, scalability and flexibility. These databases store data in various formats, such as key-value pairs or documents, and are well-suited for handling large volumes of unstructured data. Use cases for non-relational databases include social media platforms, big data analytics and content management systems.