DataTerminology.comNEW
Also known as: Redundancy
Intentional duplication of data to enhance availability, resilience, or performance across components or locations.
DESCRIPTION
Data redundancy stores multiple data copies to withstand failures, enable fast recovery, and improve read performance. Implementations include synchronous or asynchronous replication, RAID mirroring, erasure coding, and geo-redundancy. While redundancy increases reliability, it introduces costs, consistency challenges, and write amplification. In distributed systems, redundancy interacts with CAP trade-offs and failover strategies. Proper governance avoids uncontrolled duplicates that cause inconsistencies. Redundancy planning aligns with RPO/RTO objectives and compliance requirements.
ALTERNATIVE DEFINITIONS
IBM
Data redundancy occurs when identical data exists in multiple places in a database or data storage system.
Highlights duplicate data stored across multiple locations and systems.
TechTarget
Data redundancy is the presence of duplicate data in multiple places within a database or data storage system.
Focuses on redundancy inside databases and storage systems, emphasizing duplicates.
Wikipedia
Data redundancy is the duplication of data, or the storing of the same data in multiple places.
Concise definition highlighting duplication and multiple storage locations.
RELATED TERMS
Replication High Availability Durability (ACID) Backup and Recovery RAID Erasure Coding Data Deduplication Consistency Sharding Disaster Recovery
COMPETING TERMS
Feature Scaling Single Version of the Truth
KNOWLEDGE AREAS
Data Storage & Operations Data Engineering Data Architecture Cloud
TARGET AUDIENCE
Data Engineer Cloud Architect DevOps Engineer Data Architect
EXTERNAL SOURCES
- Wikipedia - Data redundancy
- IBM - Overview and best practices for redundancy
- AWS - DynamoDB global tables replication
- PostgreSQL - Streaming replication and standby
- Ceph - Erasure coding for redundancy
TOP QUESTIONS
Why is Data Redundancy important?
It improves fault tolerance, accelerates recovery, and prevents single points of failure. Redundancy also supports high read throughput and geo-access.
Category: Relevancy
When does Data Redundancy become harmful?
Uncontrolled duplicates cause inconsistencies, increased costs, and complex reconciliation. Redundancy should be intentional and governed.
Category: Risks
How does Data Redundancy relate to replication?
Replication is a mechanism that creates redundant copies across nodes or regions, either synchronously or asynchronously.
Category: Definition
What’s the difference between mirroring and erasure coding for Data Redundancy?
Mirroring duplicates data, erasure coding stores parity shards for space-efficient resilience. Erasure coding reduces storage overhead at computational cost.
Category: Example
How to manage consistency with Data Redundancy?
Define consistency models, use conflict resolution, and monitor replication lag. Eventual or strong consistency depends on business needs.
Category: Management
What’s a common mistake with Data Redundancy?
Ignoring write amplification and replication costs can degrade performance and inflate bills. Plan capacity and network impacts.
Category: Mistakes
Is Data Redundancy an alternative to backups?
No. Redundancy protects availability, backups protect recoverability and history. Both are needed for robust resilience.
Category: Misunderstanding
How do cloud providers implement Data Redundancy?
They replicate across availability zones and regions, using checksums, versioning, and automated repair to maintain durability.
Category: Overview
What metrics track effectiveness of Data Redundancy?
Replication lag, RPO, RTO, durability nines, and recovery success rates indicate effectiveness and health.
Category: Observability