Redundancy

As explained in ScyllaDB in Action

Redundancy is the inclusion of duplicate data or components so that a system can continue operating when one becomes unavailable.

Redundancy stores duplicate data or components so a system can continue serving requests when one component becomes unavailable. Multiple holders coordinate to keep their copies current. section 1.1.1

ABC Data

ABC Data assigns each customer’s data to multiple employees. If Charlotte is unavailable, Alice and Bob handle requests; when Charlotte returns, they bring her copy up to date. Three holders can require all responses for the newest answer, one for immediate availability, or two to balance correctness and availability. section 1.1.1

Figure 1.5 ABC Data’s approach gives you control over availability and correctness.

Use the figure to compare response requirements and the resulting trade-off between availability and correctness. section 1.1.1

How ScyllaDB in Action covers it

How deep it goes

Explains duplicate copies, holder coordination, unavailable nodes, scaling, and response-count trade-offs.

Examples

Uses ABC Data employees, three data holders, an unavailable Charlotte, and one-, two-, or three-holder responses.

What you can do after

Evaluate how response requirements balance immediate availability against the newest available data.

How it connects

Connects redundancy with availability, correctness, coordination, and distributed scaling.

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Also explained in

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  Machine Learning System DesignThe condition in which multiple input features provide overlapping or duplicative information.
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  Think Like a CTORedundancy is the provision of duplicate or alternative components or paths so a system can continue operating when one fails.
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  Amazon Web Services in Action, Third Edition: An in-depth guide to AWSRedundancy is the provision of multiple interchangeable components or paths so that failure of one does not interrupt service.
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  Generative AI in ActionA redundancy strategy provides duplicate or alternate system resources so service can continue when a component fails or becomes unavailable.
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  Bootstrapping Microservices, Second Edition: With Docker, Kubernetes, GitHub Actions, and TerraformRedundancy is the use of multiple equivalent instances or components so operation can continue when one fails.

Compare how 6 books explain redundancy →

Related concepts

• reliabilityproduces · Reliability is the ability of a system or process to perform its intended functions consistently and dependably under specified conditions and over time.
• single point of failureaddresses · A single point of failure is a component, dependency, person, or condition whose failure can prevent a system or critical capability from functioning because no adequate alternative is available.
• normalizationaddressed by · Normalization is the process of transforming a value, representation, or data structure to satisfy a specified standard, scale, or structural constraint.
• database normalizationaddressed by · Database normalization is a relational database design technique that organizes data into related tables to reduce redundancy and prevent update or dependency anomalies.

This explainer was generated by Manning's knowledge graph from the text of ScyllaDB in Action. The section links point to the parts of the book it draws on.