In the realm of databases, two primary types of solutions exist, SQL (relational) and NoSQL (non-relational) databases. These two categories differ significantly in their construction, the nature of the data they store, and their storage methods. Relational databases are structured with predefined schemas, while non-relational databases are unstructured, distributed, and feature dynamic schemas.
High-level differences
Here are some high-level differences between SQL and NoSQL:
Storage
SQL stores data in tables where each row represents an entity, and each column represents a data point related to that entity.
NoSQL databases utilize various data storage models, including key-value, graph, and document-oriented approaches.
Schema
In SQL, each record follows a fixed schema, which means that the columns must be determined and chosen before data entry, and each row must contain data for each column. The schema can be modified later, but this involves modifying the database using migrations.
NoSQL schemas are dynamic. Fields can be added on the fly, and each record doesn’t have to contain data for each field.
Querying
SQL databases use Structured Query Language (SQL) to define and manipulate data, which is highly powerful.
In a NoSQL database, queries focus on a collection of documents, with different databases having different syntax for querying.
Scalability
In most cases, SQL databases can be scaled vertically, which can become very costly. While it's feasible to scale a relational database across multiple servers, it's a difficult and time-consuming process.
NoSQL databases are horizontally scalable, which means it's easy to add more servers to handle large traffic. They can be hosted on inexpensive hardware or cloud instances, making them cost-effective compared to vertical scaling. Many NoSQL technologies also distribute data across servers automatically.
Reliability
The majority of relational databases are ACID compliant. Therefore, SQL databases are still the best choice for data reliability and transaction safety.
Many NoSQL solutions prioritize performance and scalability over ACID compliance.
Reasons
As always we should always pick the technology that fits the requirements better. So, let’s look at some reasons for picking SQL or NoSQL based database:
For SQL
Structured data with strict schema
Relational data
Need for complex joins
Transactions
Lookups by index are very fast
For NoSQL
Dynamic or flexible schema
Non-relational data
No need for complex joins
Very data-intensive workload
Very high throughput for IOPS
That's all folks.
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