Database Isolation Levels, ACID & Concurrency Anomalies

1. What It Is & Why It Exists

The Core Problem: Concurrency vs. Consistency Trade-off

In high-throughput transactional systems (e.g., banking transfers, inventory reservations, ride dispatch), thousands of concurrent database transactions execute simultaneously. Without isolation controls, interleaving read and write operations creates data corruption anomalies:

• Dirty Reads: Reading uncommitted data that is subsequently rolled back.
• Non-Repeatable Reads: Reading different values for the same row within a single transaction because another transaction modified and committed it.
• Phantom Reads: A query scanning a range of rows receives different row sets because another transaction inserted or deleted matching rows.
• Write Skew: Concurrent transactions read overlapping data sets, satisfy business constraints independently, and write disjoint data sets that collectively violate a global invariant.
• Lost Updates: Two concurrent transactions read a balance ($100), add$10 and $20 respectively, and write back$110 and $120, losing one transaction's increment.

Interactive Architecture Diagram
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2. Concurrency Anomalies & ANSI SQL Lattice

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Comprehensive Isolation Levels Matrix