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NoSQL Databases

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In-Memory Databases

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

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Multi-Model Databases

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

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NewSQL Databases

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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.

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Object-Oriented Databases

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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.

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Document-Oriented Databases

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

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Key-Value Stores

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

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Wide-Column Stores

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

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Time Series Databases

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Optimized for handling time-stamped data, suitable for IoT, monitoring applications, and analytics over time-series data.

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Blockchain Databases

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

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Search Engines

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

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XML Databases

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

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Event Sourcing Databases

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

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Full-Text Search Databases

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

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Graph Databases

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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.

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Mobile Databases

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

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