Distributed & Cloud Databases
Explore the dynamic world of Distributed & Cloud Databases, where scalability meets reliability. Uncover insightful resources on architectures, management techniques, and cutting-edge technologies that empower organizations to harness data efficiently across vast networks and cloud environments.
Wikipedia topics
- Distributed database This is the foundational article that defines the core concepts of databases spread across multiple physical locations.
- Cloud database This article explains database management services built and accessed through a cloud platform, essential for modern scalable applications.
- CAP theorem This theoretical framework is critical for understanding the fundamental trade-offs between consistency, availability, and partition tolerance in distributed systems.
- NoSQL This category covers non-relational database models designed for the high-velocity and high-volume data requirements often found in cloud environments.
- Database sharding This provides insight into the horizontal scaling technique of partitioning data across multiple servers to manage large datasets.
- NewSQL This describes a class of database management systems that seek to provide the scalability of NoSQL with the ACID guarantees of traditional relational databases.
- Eventual consistency This consistency model is vital for understanding how distributed systems maintain high availability by allowing temporary inconsistencies in data updates.
- Amazon DynamoDB As a seminal example of a fully managed serverless proprietary NoSQL database, it represents the industry standard for cloud-native storage.
- Google Spanner This article details a globally distributed database that manages to achieve both strong consistency and high availability at scale.
- Replication (computing) This covers the essential process of sharing information to ensure consistency between redundant resources, which is key for reliability in distributed databases.
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