Redundancy vs. Replication in a Distributed System

𝗥𝗲𝗱𝘂𝗻𝗱𝗮𝗻𝗰𝘆 - backup systems to avoid downtime.
𝗥𝗲𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 - backup data to avoid data loss.

Redundancy and replication are both strategies for increasing the reliability and availability of systems.

Redundancy

Duplicating resources to ensure uninterrupted operation in case of failure.

Redundancy is the practice of duplicating critical components or systems to increase reliability and availability. If one part fails, another seamlessly takes over. This applies to servers, databases, network devices, and even entire data centers.

𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀
→ Prevents downtime by switching to backup systems.
→ Keeps system running even during component failure.
→ Enables recovery in case of hardware or regional outages.
→ Often combined with load balancing to handle traffic across redundant systems.

𝗪𝗵𝗲𝗻 𝗧𝗼 𝗨𝘀𝗲 𝗥𝗲𝗱𝘂𝗻𝗱𝗮𝗻𝗰𝘆
• You’re building systems that must run 24/7.
• User experience and trust are tightly tied to uptime e.g. banking, trading etc.
• Legal or SLA (Service Level Agreement) requirements demand.
• Preparation for hardware failures, data center outages, or regional disasters.
• Maintenance without downtime ensures availability during updates or changes.

𝗘𝘅𝗮𝗺𝗽𝗹𝗲: 𝗣𝗮𝘆𝗺𝗲𝗻𝘁 𝗦𝗲𝗿𝘃𝗶𝗰𝗲

A payment platform has two payment processing servers in the same data center. If one server fails during a credit card transaction, the load balancer automatically reroutes the request to the backup server.

Replication
Creating multiple, identical copies of data or resources.

Replication ensures that data exists in more than one place whether across databases, servers, or regions. It helps systems stay available even when part of the infrastructure becomes unreachable.

𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀

→ Provides high availability of data, even during failures
→ Improves read performance by allowing distributed access
→ Supports disaster recovery and backup strategies
→ Enables data locality for global applications
→ Protects against data loss

𝗪𝗵𝗲𝗻 𝗧𝗼 𝗨𝘀𝗲 𝗥𝗲𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻

• You need data access across multiple regions or data centers.
• You want to scale reads across replicas.
• You’re building fault-tolerant and distributed databases.
• Regulatory requirements demand backups or geo-redundancy.
• Real-time analytics or reporting systems require up-to-date data from production.

𝗘𝘅𝗮𝗺𝗽𝗹𝗲: 𝗣𝗮𝘆𝗺𝗲𝗻𝘁 𝗦𝗲𝗿𝘃𝗶𝗰𝗲
The platform stores user balances and transaction records in a database that is replicated across multiple regions (e.g., Frankfurt and Amsterdam). If the primary database becomes unavailable, the system can read from the replica.

Conclusion
Redundancy is like an insurance policy in system design. Replication, on the other hand, ensures that data stays accessible and consistent across systems, enhancing availability, performance, and disaster recovery.