Distributed Databases: CAP Theorem and Consistency Models

Learning Objectives Define Consistency, Availability, and Partition Tolerance in the context of distributed systems. Explain the CAP Theorem and its core trade-off between consistency and availability during a network partition. Differentiate between strong consistency and eventual consistency models. Analyze a given system design problem (e.g., e-commerce vs. banking) and justify the choice of a CP or AP architecture. Evaluate the implications of choosing a specific consistency model on user experience and system performance. Ever wonder why your friend sees a new social media post seconds before you do, even though you're both online? 🤔 The answer lies in the fundamental trade-offs of distributed databases! This tutorial explores the CAP Theorem, a foundational princi...

TermDefinitionExample Distributed DatabaseA database that is not stored on a single machine, but is spread across multiple physical locations or nodes connected by a network. Each node contains a piece of the overall data.Google's Spanner or Amazon's DynamoDB are databases that run on thousands of servers worldwide, allowing for massive scale and resilience. Consistency (in CAP)Guarantees that every read operation receives the most recent write or an error. All nodes in the distributed system have the same view of the data at the same time.When you transfer money from your savings to your checking account, a consistent system ensures that anyone querying your balance sees both accounts updated simultaneously, never an intermediate state. Availability (in CAP)Guarantees that ever...

The CAP Theorem Of the three properties—Consistency (C), Availability (A), and Partition Tolerance (P)—a distributed shared-data system can simultaneously guarantee at most two. Since network partitions (P) are a fact of life in distributed systems, the theorem forces a design choice. During a partition, you must choose to either sacrifice Consistency to maintain Availability (an AP system) or sacrifice Availability to maintain Consistency (a CP system). Consistency Model Spectrum Strong Consistency <--> Eventual Consistency This isn't a binary choice but a spectrum. Strong consistency provides the freshest data but can have higher latency and lower availability. Eventual consistency provides lower latency and higher availability but at the cost of potentially sta...