Distributed Systems
How multiple independent computers cooperate to behave like one reliable, scalable system—despite failures, unreliable networks, and imperfect clocks.
In Memory Database
An in-memory database keeps the working set in RAM for sub-millisecond reads/writes, typically adding durability via logs/snapshots and HA via replication/sharding.
MongoDB
A document-oriented NoSQL database designed for flexible schemas, horizontal scaling, and developer productivity
Paxos Made Simple
Paxos is the foundational consensus algorithm that enables distributed systems to agree on values despite failures — the theoretical bedrock behind Google Chubby, Apache ZooKeeper, and every modern consensus protocol.
PostgreSQL
The world's most advanced open-source relational database, known for extensibility, standards compliance, and robust ACID transactions
Change Data Capture (CDC)
Capturing database changes for real-time replication and streaming
Google File System
Google's scalable distributed file system designed for large distributed data-intensive applications.
Leaderless Replication
Dynamo-style replication with quorums and eventual consistency
Multi-Leader Replication
Multiple writable nodes with conflict resolution strategies
Quorum Systems
Understanding quorum-based consensus mechanisms for ensuring consistency and availability in distributed systems
Raft Consensus Algorithm (Ongaro/Ousterhout) Summary
Raft protocol explained for interviews: leader election + log replication. RequestVote/AppendEntries, Raft vs Paxos, etcd/Consul use. Read now.
Single-Leader Replication
Master-slave replication with one writable leader