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Designed to handle data whose relations are well represented as a graph and suitable for social networks, recommendation engines, and fraud detection.

Combine different data models, like document, graph, and key-value, into a single, more flexible database, suitable for applications with diverse data needs.

Specialized NoSQL databases optimized for search operations, storing, and analyzing large amounts of text-heavy information; used in search platforms and text analytics.

Store and query data encoded in XML format, suitable for document-centric applications, configuration management, and situations where interoperability is key.

Store data as objects similarly to object-oriented programming, suitable for applications with complex data models and used in content management and real-time simulation systems.

Leverage blockchain technology to provide a secure and immutable data storage system, suitable for transaction histories, digital assets, and distributed ledger applications.

Use tables, rows, and dynamic columns, are highly scalable and suitable for analyzing large datasets, as in big data applications.

Use JSON-like documents, have dynamic schemas, and are good for content management and e-commerce applications.

Offer SQL-like consistency and query capabilities combined with the horizontal scaling of NoSQL systems; suitable for businesses that need high performance and scalability without sacrificing ACID properties.

Store data in main memory to offer fast read and write operations, suitable for real-time analytics and caching.

Store the sequence of events that lead to the current state of the data; used for audit trails and real-time application state reconstruction.

Designed for mobile devices, offering offline synchronization, local storage, and handling mobile-specific use cases, suitable for mobile apps with local data storage needs.

Store data as a collection of key-value pairs, are highly partitionable and support horizontal scaling, suitable for caching and session storage.

Optimized for storing, indexing, and performing search operations on text content; used in applications with advanced search features over large volumes of text.