SQL VS NoSQL DATABASES
The two main sorts of modern databases to settle on from are relational and non-relational, also referred to as SQL or NoSQL (for their query languages). There are a couple of main differences to be conversant in when deciding which database works best for your needs.
History of Relational Databases (RDBMS) and NoSQL
Relational databases (RDBMS) are around for over 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 normal SQL-based relational databases.
Data Models and Schema
NoSQL databases feature dynamic schema, and permit you to use what’s referred to as “unstructured data.” this suggests you'll 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 during a electronic database are often extremely expensive, time-consuming, and sometimes involve downtime or service interruptions.
Data Structure
Relational databases are table-based. NoSQL databases are often document based, graph databases, key-value pairs, or wide-column stores. Relational databases were built during a time that data was mostly structured and clearly defined by their relationships. Today, we know that data today is much more complex. NoSQL databases are designed to handle the more complex, unstructured data, (such as texts, social media posts, photos, videos, email) which increasingly make up much of the data that exists today.
Scaling
Relational databases are vertically scalable but typically expensive. Since they require one server to host the whole database, so as to scale, you would like to shop for a much bigger , costlier server. Scaling a NoSQL database is far cheaper, compared to a electronic database , because you'll add capacity by scaling horizontally over cheap, commodity servers.
Development Model
NoSQL databases tend to be more a neighborhood 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 far better option for contemporary applications that have more complex, constantly changing data sets, requiring a versatile data model that doesn’t got to be immediately defined. Most developers or organizations that prefer NoSQL databases, are interested in the agile features that allow them to travel to plug faster, 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 aren't capable of handling without tremendous costs, and important sacrifices of speed, agility, etc.
SQL DATABASE NoSQL DATABASE
Data Storage Model | Tables with fixed rows and columns | Document: JSON documents, Key-value: key-value pairs, Wide-column: tables with rows and dynamic columns, Graph: nodes and edges |
Development History | Developed in the 1970s with a focus on reducing data duplication | Developed in the late 2000s with a focus on scaling and allowing for rapid application change driven by agile and DevOps practices. |
Examples | Oracle, MySQL, Microsoft SQL Server, and PostgreSQL | Document: MongoDB and CouchDB, Key-value: Redis and DynamoDB, Wide-column: Cassandra and HBase, Graph: Neo4j and Amazon Neptune |
Primary Purpose | General purpose | Document: general purpose, Key-value: large amounts of data with simple lookup queries, Wide-column: large amounts of data with predictable query patterns, Graph: analyzing and traversing relationships between connected data |
Schemas | Rigid | Flexible |
Scaling | Vertical (scale-up with a larger server) | Horizontal (scale-out across commodity servers) |
Multi-Record ACID Transactions | Supported | Most do not support multi-record ACID transactions. However, some—like MongoDB—do. |
Joins | Typically required | Typically not required |
Data to Object Mapping | Requires ORM (object-relational mapping) | Many do not require ORMs. MongoDB documents map directly to data structures in most popular programming languages. |
Summary:
SQL databases are referred to as relational databases, and have a table-based arrangement , with a strict, predefined schema required. NoSQL databases, or non-relational databases, are often document based, graph databases, key-value pairs, or wide-column stores. NoSQL databases don’t require any predefined schema, allowing you to figure more freely with “unstructured data.” Relational databases are vertically scalable, but usually costlier , whereas the horizontal scaling nature of NoSQL databases is more cost-efficient.