NoSQL Databases can be described as non-tabular databases which handle data storage differently from relational tables. The data model of NoSQL databases is what distinguishes them from other types. The most popular types include column, document, key-value, and column. This article explains the types and features of NoSQL.
What is NoSQL?
NoSQL databases can be used to store data in a non-tabular way. These databases can be classified according to their data model. The most popular types are documents, graphs, and columns.
The core function of NoSQL, which is non-relational, is to provide a way for information to be stored and retrieved. Data modeling is done using methods that are not covered by the tabular relationships associated with relational database tables.
In the 1960s, NoSQL databases were in their earliest form. They were not yet known as NoSQL databases at that time. This moniker was only given to them after they became more popular in the new millennium.
NoSQL's key advantages include its flexibility and scalability. This is even possible when working with large data volumes and many users. This database class is useful in Big Data and real-time web applications.
Although the term "NoSQL" may initially have meant "non-SQL", it has become more common to be called "not only SQL" over time. This demonstrates that NoSQL can support SQL-like query language.
NoSQL's key features include a simple design, seamless horizontal scaling, as well as granular availability control. NoSQL's advantage is its ability to perform swift operations. This is due to the differences in data structures that are used in relational databases.
NoSQL sometimes sacrifices consistency for greater speed, partition tolerance, and availability. These databases can solve many business problems because of their flexibility in NoSQL data structure.
NoSQL is not without its advantages, which we will discuss in the next section. However, there are some drawbacks. NoSQL databases have a limited scope because they are primarily designed for data storage. Relational databases are better for applications like transaction management.
Moreover, two separate database systems can often be unbalanced due to a lack of accepted business standards for NoSQL. This can create problems when managing large NoSQL databases. The lack of widely-used GUI mode tools makes this even more difficult. Specific NoSQL databases store data in JSON which allows for the creation of large documents.
NoSQL Databases: Features
Although relational databases can still be used for many business functions, NoSQL databases are gaining popularity. NoSQL databases are used by companies from all industries to manage their cloud, web, and big-data applications.
NoSQL databases have the following key features:
1. Multiple Data Model Compatibility
Data in relational databases often require that data be stored in tables before they can access and analyze it. These databases are rigid in their data handling and require that information be structured before it can be ingested.
NoSQL's compatibility with multiple data formats makes it extremely flexible in data handling. It can handle structured, semi-structured, and unstructured data with equal ease and speed. This is particularly useful when specific data models are required.
NoSQL databases are favored by developers and architects because they can handle multiple Agile development needs quickly and efficiently. NoSQL supports multiple data models and allows the same data to work in multiple data models.
2. Enhanced Scalability and Accessibility
Relational databases can be scaled. Their traditional server-client architecture renders horizontal scaling resource-intensive.
NoSQL, on the other hand, can provide a peer-to-peer, serverless architecture with consistent properties across all nodes. This simplifies scaling, making NoSQL very adaptable to cloud applications. This improves performance, which allows for faster read and writes speeds as well as continuous availability.
NoSQL databases use sharding for horizontal scaling. This allows data to be divided and then placed on multiple machines. NoSQL's flexibility allows it to efficiently handle large data volumes.
The auto replication feature of NoSQL helps to ensure high availability. It responds to any failure by replicating the last known consistent state.
3. Global Data Distribution
This is possible through multiple cloud regions, data centers, and read-and-write operations at several locations.
This is in contrast to relational databases which rely on central, location-dependent applications for write and read operations. Globally distributed NoSQL databases minimize wait times by distributing multiple copies to ensure information is as close to its destination.
4. Minimal Downtime
NoSQL databases are reliable and have minimal downtime. Serverless architecture allows for multiple copies of data to remain across nodes, ensuring business continuity. A different node will allow access to the data in case of node failure.
Is NoSQL able to replace all relational databases?
No. NoSQL is best for certain use cases, while relational databases are better for other purposes. The specific needs of an organization will determine which database type is best. Enterprises can use both databases together in certain cases. Both solutions are capable to complement each other.
NoSQL is preferred by users who deal with multiple data types simultaneously. This solution is ideal for building web and cloud applications that can be used by a large, rapidly expanding community. NoSQL's flexibility, multimodality, scalability, and availability make it ideal for these applications.
For their reliability, relational databases are a common choice. They aren't always the best solution for high performance, especially when it comes to large-scale data storage and processing. NoSQL databases are gaining popularity for their high performance, accessibility, and high scalability.
NoSQL, while a robust solution that can be used to enhance existing database standards, is not meant to replace relational databases. It provides consistency and reliability in exchange for scalability, performance, and scalability. This makes it a highly specialized solution on which only a few applications can depend.
This cutting-edge database solution is available in many types and supported by popular solutions that experts have developed and are used in many verticals.