Concepts/3. Data & Storage/Database Replication (Leader-Follower) A primary leader node accepts all write transactions and streams change logs to secondary read replicas to scale read QPS and enable high availability.
STAFF ENGINEER TAKEAWAY: Asynchronous replication offers fast writes but introduces replication lag and stale reads; synchronous replication guarantees zero data loss at higher write latency.
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WAL Streaming Replication Pipeline
1
Client Write
INSERT INTO orders ...
2
Primary Leader Node
Commits locally and appends to WAL
3
Binlog Streamer
Replicates delta bytes over TCP
4
Read Replica #1 & #2
Replays WAL to serve read traffic
✓ ARCHITECTURAL ADVANTAGES
Multiplies read throughput 10x; provides instant disaster failover.
✗ TRADE-OFFS & COMPLEXITIES
Replication lag can cause users to not see their own just-written data.
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Production Systems Leveraging This Pattern
⚡PostgreSQL Streaming Replication⚡MySQL Binlog⚡AWS Aurora
More Topics in 3. Data & Storage
🗄️SQL Relational vs NoSQL Engines
SQL databases enforce structured schemas and ACID transactions with relations. NoSQL systems optimize for flexible schemas, horizontal partition scale, and eventual consistency.
🌲B-Tree & B+Tree Indexing
Self-balancing search tree data structure that keeps data sorted and allows searches, sequential access, insertions, and deletions in logarithmic O(log N) time.
🏛️ACID Transactions & Isolation Levels
Guarantees Atomicity (all-or-nothing), Consistency (rules preserved), Isolation (concurrent safety), and Durability (WAL commits survive power loss).
🔺CAP Theorem (Consistency vs Availability)
In any distributed data store, network partitions (P) are inevitable. When a partition occurs, the system must choose between Consistency (CP) or Availability (AP).