As any developer knows, the technology industry is defined by innovation discoveries and new emerging solutions. One of the most popular growing movements in current times is the switch to NoSQL databases. While not every company is moving its data storage needs to NoSQL, SQL databases dominate the industry. The past decade has seen dramatic growth in the use of NoSQL databases whether for personal projects or large-scale applications.
Although NoSQL databases have been around for decades, their prominence only came recently. Similarly, they only recently had their introduction to the professional world. With this in mind, not all developers and engineers have had exposure to such differences. Thus, for a quick rundown on NoSQL databases, check out the following key differences between SQL databases and the former.
Structured Query Language
SQL databases get their clever name from the use of structured query language. Developers interact directly with the data and the database via SQL. They can query for information, update information, and add new information using the language. The beauty of the language is that developers can use it across all SQL databases.
In a vaguely similar naming convention, NoSQL databases also derive their name from structured query language, but it provides a different meaning— “not only SQL. The name comes from the fact that some NoSQL databases support the use of SQL. However, in general, NoSQL databases do not use SQL. Rather, many similar languages take inspiration from SQL’s terms like select and join.
Database Design
For an SQL database to operate efficiently, especially for large applications, the database must be designed. That typically takes the skills of a database designer or architect. This design incorporates creating the tables, fields, primary keys, secondary keys, and more.
In comparison, NoSQL databases do not need to be designed in the same sense. Rather, the database can be constructed on the fly. NoSQL databases can store information in documents, key-value pairs, graphs, and column-oriented databases. None of these types require much initial planning. The reason for this lack of planning will be seen with insight provided from the following key difference!
The Use of Schemas
SQL databases make use of schemas and pre-defined tables. Inside each table, data points will have primary IDs that act as identifiers for all the information they’re associated with. These IDs can be placed inside of other tables as secondary IDs which then create relationships between different tables. These schemas and relationships are why SQL databases are also called relational databases—they form easily identifiable relationships between tables.
NoSQL databases are essentially the opposite. They do not use schemas, and they’re also known as non-relational databases. Rather than using schemas and tables, NoSQL databases store data in unique ways that depend upon what kind of NoSQL database is being used. One of the most common NoSQL systems, document stores, stores data in JSON-like objects. This makes it extremely easy for developers to use.
Another strong selling point of these schema-free databases is that their stores can change on the fly. Each data point in a store may contain vastly different information, just like you could see in a JSON object.
Scaling
One of the largest drawbacks of SQL databases is vertical scaling. When an application needs more data storage, these databases must add components and hardware to increase capacity or performance. Eventually, a limit is reached where no more hardware can be added. This point can be expensive to readjust the database.
On the other hand, NoSQL databases scale horizontally. The database is spread out over computers, or nodes. When storage needs increase, computers can be added to the system to increase capacity. This is much easier, quicker, and cheaper.
ACID vs BASE
Developers have likely heard the term ACID. It stands for atomic, consistency, isolated, and durable. SQL databases follow ACID, so they can provide safe and reliable data storage. The goal of this is for data to be consistent throughout the database for all users at all times.
In contrast, NoSQL databases follow BASE‑basically available, soft-state, and eventual consistency. BASE is a looser, more flexible version of ACID. Essentially, NoSQL databases do not guarantee consistency at all times. However, eventually, the database will become consistent.
It is important to note that BASE and ACID are not two of the same—their principles differ and cannot be compared one-to-one.
The Bottom Line
NoSQL and SQL databases greatly differ on many points. One is not better than the other, but just like any technology, eventually, developers will have their preferences. Luckily, there are numerous options for database selection for both SQL and NoSQL databases. While each type offers several benefits, you must understand your needs and the databases to properly select which database to use.
About the Author
Alex Williams, Writer/Researcher at Hosting Data UK, is a seasoned full-stack developer and an expert on all things NoSQL.
Sign up for the free insideBIGDATA newsletter.
Join us on Twitter: @InsideBigData1 – https://twitter.com/InsideBigData1
Speak Your Mind