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What is NoSQL? - Definition & Meaning

Learn what NoSQL databases are, how they differ from SQL, and when to choose a non-relational database. Discover document, key-value, and graph databases.

Definition

NoSQL (Not Only SQL) is an umbrella term for database systems that use a data model other than traditional relational tables. NoSQL databases offer flexible schemas and are designed for horizontal scalability, high availability, and processing large volumes of unstructured or semi-structured data.

Technical explanation

NoSQL databases are divided into four main categories. Document databases like MongoDB store data as JSON-like documents, ideal for content management and product catalogs. Key-value stores like Redis offer ultra-fast storage for session data and caching. Column-family databases like Apache Cassandra are optimized for write-intensive workloads and time-series data. Graph databases like Neo4j model relationships between entities and excel at recommendation systems and social networks. NoSQL databases often follow the BASE model (Basically Available, Soft state, Eventually consistent) instead of the stricter ACID model of SQL databases. This enables horizontal scalability through sharding, where data is distributed across multiple servers. Many NoSQL databases support automatic replication for high availability. The absence of a fixed schema (schema-less) offers flexibility but requires discipline in the application layer to ensure data consistency.

How MG Software applies this

At MG Software, we deliberately choose the right type of database for each project. For most projects, we use PostgreSQL (SQL) as the primary database, but we integrate NoSQL solutions where they add value. We use Redis for caching and real-time session data. For projects with highly variable data structures or high write volumes, we recommend MongoDB. We help clients make the right choice and implement hybrid architectures that combine the best of both worlds.

Practical examples

  • A social media platform using MongoDB to store user profiles, where each profile can contain a different set of fields such as interests, location, and media preferences without a fixed schema constraining it.
  • A gaming company using Redis as a key-value store for real-time leaderboards and session data, with sub-millisecond response times for millions of concurrent players.
  • A recommendation engine using Neo4j to model relationships between users, products, and purchase behavior, generating personalized suggestions based on graph algorithms.

Related terms

sqlbackendcloud computingmicroservicesapi

Further reading

Learn about SQLWhat is Backend development?What is Cloud Computing?

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Frequently asked questions

Choose NoSQL when dealing with unstructured data that does not fit well in tables, when you need extreme horizontal scalability, or when your data model evolves rapidly. For structured data with complex relationships and strong consistency requirements, SQL is often the better choice. Many modern applications combine both types.
Not necessarily. NoSQL databases are faster for specific patterns they are designed for, such as key-value lookups or document storage. SQL databases perform better with complex queries involving multiple joins and aggregations. Speed depends on the usage pattern, data model, and how well the database is configured.
Yes, this is called polyglot persistence. Many modern applications use a SQL database as the primary data store for structured business data and a NoSQL solution for specific tasks like caching (Redis), full-text search (Elasticsearch), or real-time analytics. This hybrid approach leverages the strengths of each type.

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