Overview and Definitions: Relational databases would provide a store of related data tables. These tables have a fixed schema and use SQL to manage its data. NoSQL databases refer to high$-$performance, non$-$relational data stores. They excel in their scalability, availability and ease$-$to$-$use of their database.

Data Modeling: Relational databases would use structured schemas and tables to enforce data integrity and relationships, however the predefined schemas can't be changed and it does struggle with scalability. NoSQL databases offer flexible schemas and horizontal scaling. It makes them ideal for holding large volumes of unstructured data. However, in a NoSQL database, it would often lack the strong consistency and complex querying features of relational databases.

Query Languages: The query language used in relational databases is SQL mainly, as it is by far the most popular and commonly used query language for relational databases. NoSQL databases does not have a go to query language however they used JSON $($JavaScript Object Notation$),$ XML$,$ YAML, or binary schema.

Scalability and Performance: For relational databases, they scale vertically, meaning they enhance performance by adding in resources to a single server and perform well because of their strong ACID $($Atomicity$,$ Consistency, Isolation, Durability$)$ properties. For example, Facebook used MySQL for storing social graph data. For NoSQL databases, they excel at horizontal scaling, where data is distributed across multiple servers. For example, at Netflix, they used Cassandra for its distributed and highly available architecture.

Data Integrity and Transactions: Relational databases ensure data integrity through ACID properties by guaranteeing reliable and consistent transactions while NoSQL databases prioritize availability and partition tolerance, which allows scalability and highly available systems.

Use Cases: For relational databases, it would be useful for e$-$commerce websites since they need it to handle structured data like user accounts, product inventories and transaction records. Another example would be a healthcare management system as they require stringent data integrity and consistency for patient records, treatments histories, and billing information. For NoSQL databases, gaming applications would be good since they require high performance and scalability to handle all their user data, game statistics and real time interactions. Another example would be a real time analytics platforms as they are needed to process and analyze large volumes of unstructured data quickly.

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