NoSQL
Also written: Not Only SQL
Databases that don't use tables, good for large, varied, or fast-changing data.
NoSQL databases are a different way to store and manage data compared to traditional databases.
Instead of using tables with rows and columns like in relational databases, NoSQL databases can use various structures like documents, key-value pairs, or graphs. This flexibility makes them well-suited for handling large amounts of data that might not fit neatly into tables, such as user profiles, sensor readings, or social media posts. For example, a social media platform might use a NoSQL database to store user posts and connections because the data is constantly changing and can be very diverse.
NoSQL, or 'Not Only SQL,' refers to a broad class of database systems that deviate from the traditional relational model. These systems are designed to overcome limitations of relational databases in terms of scalability, flexibility, and performance, particularly for large-scale, distributed, and rapidly evolving datasets.
Key characteristics include schema flexibility, horizontal scalability (scaling out by adding more machines), and often a focus on specific data models like document stores (e.g., MongoDB), key-value stores (e.g., Redis), column-family stores (e.g., Cassandra), or graph databases (e.g., Neo4j). Tradeoffs often involve weaker consistency guarantees compared to ACID-compliant relational databases, and a different query paradigm.
NoSQL databases are crucial for modern AI applications that process vast and diverse datasets. Their ability to scale and handle unstructured data supports the massive training and inference demands of frontier AI models. Microsoft's mention highlights how these databases are essential for building AI-ready infrastructure, enabling faster development and deployment of AI features.
- What customers value most in Microsoft Databases—from reliability to AI readinessMicrosoft · Microsoft Azure Blog ·
- Microsoft Copilot
- Microsoft offers various database solutions, including those supporting NoSQL principles, which are highlighted for their reliability and AI readiness.
- SQL
- SQL databases use a structured, table-based relational model with predefine
- NewSQL
- NewSQL databases aim to combine the scalability of NoSQL with the ACID g
The term 'NoSQL' emerged in the early 2000s within the open-source community as a way to describe a growing number of non-relational database systems. It gained prominence around 2009. Source ↗
Explore a document database by trying to store information about a collection of books. Each book could be a document with fields like title, author, and genre, and you can add custom fields for each book without changing a central structure. Many cloud providers offer free tiers for NoSQL database services like Amazon DynamoDB or Azure Cosmos DB, where you can create a simple table and add documents to see how it works.
The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.
- PromptRole-play a student struggling with math for AI tutor simulationSimulate a student's math struggles and uncertainty for AI tutor evaluation. · 5 min
- TemplateReusable workflow templates for healthcare teamsTeams can create and share templates for common workflows like documentation or prior authorizations. · 15 min
- TemplateTemplate for building an AI tool tailored to your workA structured approach to defining and building a custom AI tool for specific business needs. · 15 min
- TemplateEvals CSV prompt list for agent skillsA CSV file template for listing prompts used in evaluating agent skills. · 20 min
- HeuristicDouble coding agent task completion with docs linksProviding coding agents with a documentation link significantly increases their task completion rate. · 2 min
Questions people ask
- What does 'NoSQL' stand for?
- It originally stood for 'No SQL' but is now often interpreted as 'Not Only SQL,' reflecting that these databases can coexist with or complement SQL databases.
- When should I use NoSQL instead of SQL?
- Use NoSQL for applications needing high scalability, flexible data models, or handling large volumes of unstructured or semi-structured data, especially when rapid development is key.
First seen on Subvolts Jul 27, 2026. Updated Sep 15, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.