---
title: SQL vs. NoSQL databases
description: Learn about the differences between SQL and NoSQL, each with a unique set of benefits suited for particular use cases.
url: /kb/guide/sql-vs-nosql-databases
canonical_url: "https://vercel.com/kb/guide/sql-vs-nosql-databases"
published: 2025-11-03
last_updated: 2025-11-10
authors: Lydia Hallie
related: []
install_vercel_plugin: npx plugins add vercel/vercel-plugin
---
<!-- docsgraph:related -->
## Related pages

> **For AI agents:** Follow these links to understand how this page connects to the rest of the Vercel ecosystem. For the full cross-link map (inbound, outbound, prerequisites, and semantic neighbors), see the .graph.md link below.

- [Comparing MySQL, PostgreSQL, and MongoDB ](https://vercel.com/kb/guide/mysql-vs-postgresql-vs-mongodb?from=related) — Explore database selection for optimal performance, focusing on SQL options like MySQL, PostgreSQL, and NoSQL's MongoDB.
- [Marketplace](https://vercel.com/docs/marketplace-storage?from=related) — Connect Postgres, Redis, NoSQL, and other storage solutions through the Vercel Marketplace. Run SQL queries, edit data,
- [Overview](https://vercel.com/docs/storage?from=related) — Store large files and global configuration with Vercel's storage products.
- [Backends](https://vercel.com/docs/frameworks/backend?from=related) — Vercel supports a wide range of the most popular backend frameworks, optimizing how your application builds and runs no
- [Comparisons](https://workflow-sdk.dev/docs/comparisons?from=related) — Side-by-side comparisons of the Workflow SDK against Temporal, Cloudflare Workflows, AWS Step Functions, AWS Bedrock Age
- [Notebooks](https://vercel.com/docs/notebooks?from=related) — Learn more about Notebooks and how they allow you to organize and save your queries.
- [Vector Databases Explained](https://vercel.com/kb/guide/vector-databases?from=related) — Learn about vector databases: what they are, 8 of the best examples and how to build an AI semantic search app with them
- [Is SQLite supported in Vercel?](https://vercel.com/kb/guide/is-sqlite-supported-in-vercel?from=related) — SQLite is a popular and fast database engine. In this article, we discuss whether it can be used in a serverless environ
- [Connect Next.js to Amazon Aurora PostgreSQL using Vercel Marketplace](https://vercel.com/kb/guide/connect-next-js-to-amazon-aurora-postgresql-using-vercel-marketplace?from=related) — Learn how to connect your Next.js application to Amazon Aurora PostgreSQL securely using the Vercel Marketplace AWS inte
- [Using a Headless CMS with Vercel](https://vercel.com/kb/guide/using-a-headless-cms-with-vercel?from=related) — Learn best practices for using databases in a serverless environment with Vercel

Full cross-link map for this page: [/kb/guide/sql-vs-nosql-databases.graph.md](/kb/guide/sql-vs-nosql-databases.graph.md)
<!-- /docsgraph:related -->


The choice of a database can significantly influence the performance, functionality, and scalability of your application. This guide provides a deep dive into the differences between two important paradigms, SQL and NoSQL, each with a unique set of benefits suited for particular use cases.

* * *

## SQL databases

Structured Query Language (SQL) is a standardized language for managing and querying data in **relational databases**. Such databases organize data into tables consisting of rows and columns. Each table typically represents a distinct entity, and SQL helps define and manipulate relationships between these entities. The query language is the means by which you interact with the data. You can perform various operations like adding new data (**`INSERT`**), updating existing data (**`UPDATE`**), deleting data (**`DELETE`**), or retrieving data (**`SELECT`**) using different queries.

Various database management systems like [MySQL](https://www.mysql.com/) and [PostgreSQL](https://www.postgresql.org/) use SQL as their query language.

```bash
CREATE TABLE users (
    userId INT PRIMARY KEY,
    name VARCHAR(255),
    age INT,
    email VARCHAR(255)
);

CREATE TABLE cities_lived (
    userId INT,
    city VARCHAR(255),
    FOREIGN KEY (userId) REFERENCES users(userId)
);

INSERT INTO users (name, age, email) VALUES ('John', 30, 'john@doe.com');

INSERT INTO cities_lived (userId, city) VALUES
    ((SELECT userId FROM users WHERE email = 'john@doe.com'), 'New York'),
    ((SELECT userId FROM users WHERE email = 'john@doe.com'), 'Los Angeles');
```

SQL databases prioritize accuracy, integrity, and relationship enforcement, often encapsulated in a structured, predefined schema.

They were primarily designed for vertical scalability, which means enhancing the server's hardware capabilities for improved performance. For example, you could upgrade the server with a faster CPU, more RAM, or faster storage.

However, these databases also support horizontal scaling through _data sharding_. This involves partitioning the database into smaller, more manageable pieces; shards. Shards can be distributed across a multitude of servers and enable the system to handle increased traffic and data volumes without compromising performance.

* * *

SQL databases are ACID compliant. This means that they adhere to a set of properties— Atomicity, Consistency, Isolation, Durability — which strengthen data integrity and transaction management, which is necessary for applications in which data accuracy and reliability are crucial.

- **A****tomicity:** Every transaction is treated as a singular unit, ensuring complete success or failure.
  
- **C****onsistency:** Only valid data is written to the database, maintaining system integrity.
  
- **I****solation:** Concurrent transactions are processed in a way that the outcome is the same as if they were processed individually, preventing potential interference.
  
- **D****urability:** Committed transactions persist, even during system failures.
  

Applications where data consistency and accuracy are paramount, like financial or medical record systems, often opt for SQL databases.

* * *

## NoSQL Databases

NoSQL (_"__N__ot_ _O__nly_ _SQL__"_) databases provide more flexibility in handling unstructured or semi-structured data. These databases don't require a fixed schema.

Querying methods can vary among NoSQL databases. [MongoDB](https://www.mongodb.com/), for example, uses a method-based query language that is JavaScript-like in its syntax:

```bash
db.collection('users').insertOne({
    name: 'John',
    age: 30,
    email: 'john@example.com',
    cities_lived: ['New York', 'Los Angeles']
});
```

NoSQL databases are optimized for specific tasks that require more flexibility, like document storage, key-value pairs, or graph-based relationships. They prioritize horizontal scalability, which is achieved through techniques like sharding or partitioning — distributing data across multiple servers to accommodate more traffic. This design caters to high-throughput, web-scale applications dealing with large data volumes.

Unlike SQL where data normalization necessitates separate tables, NoSQL databases simplify this by allowing related data to be stored together, reducing query complexity.

#### Horizontal Sharding

Horizontal sharding involves distributing rows of data **across multiple servers**, so each server contains all the necessary columns but for a subset of users. This approach is great for NoSQL databases, as it allows them to distribute large datasets across multiple servers or clusters, enhancing horizontal scalability.

However, the fact that NoSQL databases can store related data together can be less space-efficient and can make aggregations more challenging.

In SQL, aggregations and JOIN operations are more straightforward, with structured, normalized data facilitating complex queries. In NoSQL, however, you might need to create an index to support more complex aggregations. It's a trade-off between query complexity and scalability.

* * *

NoSQL databases usually follow the CAP theorem:

- **C****onsistency:** Similar to ACID’s consistency, ensuring data remains consistent post-transactions across a distributed system.
  
- **A****vailability:** The system remains operational for both reads and writes, even during network partitions.
  
- **P****artition Tolerance:** The system operates despite network partitioning, a common occurrence in distributed systems due to various network issues.
  

**Network partitioning** is a communication breakdown within a distributed system—imagine a bunch of interconnected computers suddenly losing touch with some others in the group. This scenario is common in distributed setups due to network-related issues such as router failures, switch failures, or other network hardware problems.

According to the CAP theorem, databases can guarantee only two of these three attributes during network partitioning.

Trade-offs among these properties depend on system requirements. For example, prioritizing consistency and partition tolerance may result in intermittent unavailability for reads and writes.

* * *

[In another guide](https://vercel.com/guides/mysql-vs-postgresql-vs-mongodb), we explore the differences between popular SQL and NoSQL choices like MySQL, PostgreSQL, and MongoDB.