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NoSQL vs. Relational Databases

The two main types of modern databases to choose from are relational and non-relational, also known as SQL or NoSQL (for their query languages). There are a few main differences to be familiar with when deciding which database works best for your needs.

TL;DR summary:

SQL databases are known as relational databases, and have a table-based data structure, with a strict, predefined schema required. NoSQL databases, or non-relational databases, can be document based, graph databases, key-value pairs, or wide-column stores. NoSQL databases don’t require any predefined schema, allowing you to work more freely with “unstructured data.” Relational databases are vertically scalable, but usually more expensive, whereas the horizontal scaling nature of NoSQL databases is more cost efficient.

  1. History of relational databases (RDBMS) and NoSQL
  2. Relational databases (RDBMS) have been around for more than 40 years. Historically, they’ve worked well, for the times when data structures were much more simple and static. However, as technology and big data applications advanced, the traditional SQL-based relational database was less equipped to handle rapidly expanding data volumes and the growing complexities of data structures. In the last decade, the non-relational NoSQL databases became more popular for offering a more flexible, scalable, cost-efficient alternative to the traditional SQL-based relational databases.

  3. Data models and schema
  4. NoSQL databases feature dynamic schema, and allow you to use what’s known as “unstructured data.” This means you can build your application without having to first define the schema. In a relational database, you are required to define your schema before adding data to the database. Not needing a predefined schema makes NoSQL databases much easier to update as data and requirements change. Changing the schema structure in a relational database can be extremely expensive, time consuming, and often involves downtime or service interruptions.

  5. Data structure
  6. Relational databases are table-based. NoSQL databases can be document based, graph databases, key-value pairs, or wide-column stores. Relational databases were built during a time when data was mostly structured and clearly defined by its relationships. Today, we know that data is much more complex. NoSQL databases are designed to handle the more complex, unstructured data (such as texts, social media posts, photos, videos and email), which increasingly make up much of the data that exists today.

  7. Scaling
  8. Relational databases are vertically scalable but typically expensive. Since they require a single server to host the entire database, in order to scale, you need to buy a bigger, more expensive server. Scaling a NoSQL database is much cheaper, compared to a relational database, because you can add capacity by scaling horizontally over cheap commodity servers.

  9. Development model
  10. NoSQL databases tend to be more a part of the open-source community. Relational databases are typically closed source with licensing fees baked into the use of their software.

Common NoSQL vs relational database (aka SQL) questions

Is NoSQL better than SQL?

  • NoSQL tends to be a better option for modern applications that have more complex, constantly changing datasets, requiring a flexible data model that doesn’t need to be immediately defined. Most developers or organizations that prefer NoSQL databases are attracted to the agile features that allow them to go to market faster and make updates faster. Unlike traditional, SQL-based, relational databases, NoSQL databases can store and process data in real time.
  • While SQL databases do still have some specific use cases, NoSQL databases have many features that SQL databases are not capable of handling without tremendous costs and critical sacrifices of speed, agility, etc.

What are the major differences between NoSQL and SQL?

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