CAPTheorem
The CAP theorem states that a distributed data system can provide at most two of three guarantees simultaneously during a network partition: Consistency, Availability, and Partition Tolerance.
26 resources across 3 libraries
Glossary Terms(9)
System Design
System design is the process of defining the architecture, components, interfaces, and data flow of a software system to satisfy specified functional and non-f…
DBMS
A Database Management System (DBMS) is software that provides an interface for creating, storing, querying, and managing data in databases, handling concerns l…
ACID Properties
ACID is an acronym describing four guarantees — Atomicity, Consistency, Isolation, and Durability — that traditional relational database transactions provide t…
CAP Theorem
The CAP theorem states that a distributed data system can provide at most two of three guarantees simultaneously during a network partition: Consistency, Avail…
Sharding
Sharding is a database scaling technique that splits a large dataset horizontally across multiple independent database instances (shards), each holding a subse…
Database Replication
Database replication is the process of copying and synchronizing data from a primary database to one or more secondary databases, used to improve read scalabil…
NewSQL
NewSQL is a class of database systems that aim to provide the horizontal scalability of NoSQL databases while retaining the ACID transactional guarantees and f…
Distributed Systems
A distributed system is a collection of independent computers that appear to their users as a single coherent system, coordinating over a network to achieve sh…
CAP Theorem (CS)
The CAP theorem states that a distributed data store can provide at most two of the following three guarantees simultaneously during a network partition: Consi…
Cheat Sheets(1)
Interview Questions(16)
What is CAP Theorem?
CAP theorem states that a distributed data store can only guarantee two of three properties at once — Consistency, Availability, and Partition tolerance — duri…
What is Quorum-Based Replication for Reads and Writes?
Quorum-based replication requires a write to be acknowledged by a minimum number of replicas (W) and a read to consult a minimum number of replicas (R) out of…
What is Eventual Consistency in Databases?
Eventual consistency is a consistency model where, after writes stop arriving, all replicas of a piece of data are guaranteed to converge to the same value eve…
Strong Consistency vs Eventual Consistency: What is the Difference?
Strong consistency guarantees that any read immediately after a write returns that write's value everywhere, while eventual consistency allows reads to briefly…
What is Tunable Consistency and the N/R/W Quorum Model in NoSQL?
Tunable consistency lets a distributed NoSQL store trade consistency for availability and latency per-request, using three configurable numbers: N (replicas ho…
What Is the Split-Brain Problem in Distributed Databases?
Split-brain occurs when a network partition or failed failover causes two nodes in a distributed database cluster to each believe they are the sole primary and…
What is a Distributed File System?
A distributed file system presents files stored across multiple networked machines through a single unified namespace, so clients read and write remote files u…
SQL vs NoSQL for Scale: Which Should You Choose?
SQL databases scale best when data is relational and consistency matters, typically via vertical scaling or read replicas, while NoSQL databases are built to s…
What is Eventual Consistency?
Eventual consistency is a consistency model in which, if no new updates are made to a piece of data, all replicas will converge to the same value over time, th…
How to Design a Distributed Key-Value Store
A distributed key-value store is designed by partitioning keys across nodes with consistent hashing, replicating each key to N nodes for fault tolerance, and c…
What is the CAP Theorem and What Trade-offs Does It Force?
The CAP theorem states that a distributed data store can provide at most two of Consistency, Availability, and Partition tolerance at the same time, and since…
What is the PACELC Theorem and How Does It Extend CAP?
PACELC extends the CAP theorem by pointing out that even when there is no network partition, a distributed system still has to trade off Latency against Consis…
Strong Consistency vs Eventual Consistency: How Do You Choose?
Strong consistency guarantees that every read returns the most recently written value across all replicas, typically by requiring writes and reads to coordinat…
How Do You Design a Multi-Region Deployment?
A multi-region deployment runs a system's services and data across geographically separate cloud regions, typically to cut latency for global users and to surv…
What Are Network Partitions in Distributed Systems?
A network partition occurs when a communication failure splits a distributed system into two or more groups of nodes that can no longer reach each other, even…
What Are Geo-Replication Strategies?
Geo-replication is the practice of copying data across data centers in different geographic regions, so reads and writes can be served locally near users while…