🗄️ Distributed Database Simulator
Visualize node replication, CAP theorem tradeoffs, and consistency propagation
🤔 What Is a Distributed Database?
A distributed database spreads data across multiple servers (nodes) in different locations. The CAP theorem says you can only guarantee two of three properties: Consistency (every read sees the latest write), Availability (every request gets a response), and Partition Tolerance (the system works despite network splits).
Why does this matter? Every major internet service from Google to Netflix relies on distributed databases. Understanding the tradeoffs between consistency and availability is essential for building reliable, scalable systems that serve billions of users.
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Replication
Copy data across nodes for fault tolerance
⚖️
CAP Theorem
Consistency vs Availability tradeoffs
📊
Quorum Voting
Majority-based read/write consensus
🔌
Network Partitions
Handling split-brain scenarios
⏱️
Eventual Consistency
Propagation delay visualization
🗃️
Conflict Resolution
LWW, CRDTs, and vector clocks
🚀 Quick Start
⚙️ Basic Settings
📋 Event Log
Cluster idle. Press Start...
Reads/s: 0
Writes/s: 0
Repl Lag: 0 ms
Consistency: 100%
Avail Nodes: 5/5
Conflicts: 0