Accepts inventory writes
Cloud / Knowledge library
Data Replication
Maintains copies of data or logs across multiple nodes
Why learn Data Replication?
It improves availability, locality, and read capacity
The problem it solves
It keeps services operating when a storage node becomes unavailable
Where it came from
Data Replication is a distributed systems concept that maintains copies of data or logs across multiple nodes. Its guarantees and tradeoffs depend on the concrete implementation and operating context.
Build your understanding
Work through these exercises in order. Try the task before opening a reference.
- Define Data Replication and distinguish it from a neighboring concept.
- Choose a realistic task where Data Replication is appropriate.
- Identify a failure mode caused by misusing Data Replication.
- Interpret a small design or result involving Data Replication.
- Explain one tradeoff or limitation of Data Replication.
Documentation and sources
- Designing Data-Intensive Applications (dataintensive.net)
Connect the ideas
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Real World Example
Regional Inventory Synchronization for Global Retail
A global retail chain managing inventory across multiple geographically distributed warehouses needs to ensure that stock levels remain consistent for online orders.
The business problem
If a single warehouse node fails or experiences network partitioning, the central system loses visibility into local stock, leading to overselling or inventory discrepancies that disrupt customer fulfillment.
How this topic solves it
Data replication maintains copies of data across multiple nodes, ensuring that if one node becomes unavailable, the system can route requests to a replica that holds the current state of inventory records.
- Identify the primary node responsible for accepting write operations for specific inventory regions.
- Configure follower nodes to asynchronously pull log updates from the primary node to maintain local copies.
- Implement a consensus-based protocol to ensure that replicas acknowledge the receipt of data updates.
- Set up automated failover mechanisms that promote a follower node to primary status if the original primary node stops responding.
This diagram illustrates how a primary node propagates inventory updates to multiple follower nodes to ensure data redundancy.
Maintains data copy
Maintains data copy
- Primary Node → Replicates log → Follower Node 1
- Primary Node → Replicates log → Follower Node 2
Expected business outcome
The system achieves higher availability and fault tolerance, allowing the retail chain to process orders even if a specific regional warehouse server is temporarily offline.
Limitations and checks
The primary limitation is the potential for replication lag, where follower nodes may temporarily hold stale data; this can be checked by monitoring the time difference between the latest log entry on the primary and the last applied entry on the replica.