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A while back here on the blog, our article ‘Some Basic SQL Queries’ provided beginner-friendly commands for building and deploying SQL databases. These databases have long been popular in the programming community as the syntax and storage logic used are straightforward and reliable. It’s no wonder they remain suited for virtually any industry across a wide variety of applications. These range from generic purposes like maintaining employee records to more specialized tasks like using Apache Impala, powerful software for fields such as data science. However, SQL databases are not the only option. In fact, there are many varieties which are known as NoSQL which have some key differences from SQL ones. In this article, we cover the main differences between NoSQL vs. SQL databases to help you make a better decision when it comes to database selection for your application.
History of SQL
The widespread use of SQL databases began not long after Relational Software, Inc. – Oracle’s predecessor – released its own SQL version named Oracle V2 in 1979. The technology evolved continuously in the years that followed, speeding up adoption among business and personal users. In terms of relational database communication today, SQL remains the industry standard.
The Rise of NoSQL
In recent years, however, another type of database known as NoSQL or “Not only SQL” has also become popular. Scalability, support for unstructured data, and handling very large volumes of information are among its defining characteristics. As such, it’s a preferred choice of big companies such as Netflix and Facebook that handle comprehensive projects like image/video aggregation and social media networking.
The NoSQL concept was developed by Carlo Strozzi in 1998, although it didn’t receive mainstream attention until 2009 when software engineers Johan Oskarsson and Eric Evans held an event about open-source non-relational databases. With extensive dev work and other technological innovations along the way, NoSQL quickly became a popular option for database needs.
Key differences
To know which type better fits your needs, you must first distinguish the differences between the two types:
Data Storage and Design Principles
SQL databases follow a table-based storage format, consisting of fixed rows and columns. Information is captured, processed, sorted, and/or retrieved by means of primary and foreign keys. It follows predefined, rigid schemas meaning it primarily deals with structured data, such as accounting records for example.
The main design principle of SQL databases is the ACID consistency model, which stands for Atomicity, Consistency, Isolation, and Durability. One guide on SQL vs. NoSQL databases notes that ACID is the gold standard for relational database management systems. It ensures that data is stable and consistent even if used in numerous memory locations.
NoSQL databases have four main kinds, namely Document, Key-value, Wide-column, and Graph. Each follows its own storage format, and respectively these are JSON documents; key-value pairs; tables with rows and dynamic columns; and nodes and edges. NoSQL databases also have flexible schemas, hence their advantage in dealing with unstructured data, such as video files.
Most NoSQL systems employ the BASE consistency model, which stands for Basically Available, Soft-state, Eventually consistent. It works by duplicating data in multiple storage systems to ensure they’re always available. These duplicates may not be consistent all the time, which means they’re at a soft-state, but will be consistent at some point.
Hardware and Scaling
Because SQL databases typically function within one server, they usually require specialized database hardware. That is a common practice, especially for businesses or users that manage large volumes of data. A post on NoSQL and SQL databases by MongoDB explains that this entails vertical scaling if an upgrade is necessary to accommodate project requirements. You need to procure a more powerful server with bigger storage capacity.
NoSQL databases can function on commodity hardware connected to conduct data interchange. Numerous servers with relatively lower specs can be set up to meet the same requirements for one high-capacity server. Scaling can be more cost-effective as it’s done horizontally, which means adding more commodity hardware to the network.
Conclusion
In this article, we provided a guide to the main differences between NoSQL vs. SQL databases. In general, both types of database have their advantages and suitable use-cases so it doesn’t mean that one is better than the other. It ultimately boils down to your project requirements.
For additional support, check out other database related articles here on Geeky Hacker.
