Distributed databases store data across multiple physical locations to improve data availability, reliability, and performance. They enable concurrent data access and processing, but require complex mechanisms for data consistency, replication, and coordination among distributed nodes.

Distributed Databases

Distributed databases

Data availability refers to the ease with which data can be accessed and used by authorized users, ensuring that it is consistently retrievable and usable when needed. It is a critical aspect of data management that impacts decision-making, operational efficiency, and the overall reliability of information systems.

data availability

Data reliability refers to the consistency and dependability of data over time, ensuring that it is accurate, complete, and can be trusted for decision-making. High data reliability minimizes errors and biases, which is crucial for effective analysis and meaningful insights.

Data Reliability

Data Performance

concurrent data access

Data processing involves the collection, transformation, and organization of data to extract meaningful insights and facilitate decision-making. It encompasses a range of activities, from data cleaning and integration to analysis and visualization, ensuring data is accurate, accessible, and actionable.

Data Processing

Data consistency ensures that data remains accurate and reliable across a system, preventing discrepancies and errors during data processing and retrieval. It is crucial for maintaining data integrity, especially in distributed systems where multiple sources may update the same data concurrently.

data consistency

Data replication involves creating and maintaining multiple copies of data across different locations to ensure availability, reliability, and redundancy. It is crucial for disaster recovery, load balancing, and improving access speed in distributed systems.

CUSTOMIZE YOUR LEARNING

CUSTOMIZE YOUR LEARNING

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