Prerequisites
What it is
Strong consistency means once a write commits, later reads observe that write. The system presents a single up-to-date view even if data is replicated internally.
Why it matters
Some decisions cannot safely use stale data: payments, authorization, inventory, account state, ownership, and compliance records often need strong guarantees.
How it works
Systems use leaders, consensus, transactions, locks, quorum reads/writes, or serializable databases to coordinate access before acknowledging success.
When to use it
Use it when stale reads could cause financial loss, data leaks, double spending, incorrect permissions, or irreversible user harm.
Tradeoffs / failure modes
Coordination adds latency and can reduce availability during partitions. Overusing strong consistency makes large systems slower and harder to scale.
Tiny example
Before letting a user delete a repository, GitHub must read current permissions from an authoritative source rather than a stale cache.
Related guides and systems
See Payment Processing, RBAC, Audit Logging, GitHub, Gmail, and Google Drive.
Seen in deeper dives
Capability
Audit Logging
Append-only event stores, tamper-proof records, and compliance-ready activity trails
Capability
Payment Processing
Idempotent charges, webhook reconciliation, and PCI compliance for online payments
Capability
Role-Based Access Control
Permission models, policy engines, and row-level security for multi-user applications
Case Study
GitHub
The world's largest code hosting platform powered by Git at scale
Case Study
Gmail
The world's largest email service with AI-powered organization and search
Case Study
Google Drive
Cloud file storage and real-time collaboration at planetary scale
Related concepts
Write-Through Cache
Keep cache and database updated together so reads can trust the cached value.
Eventual Consistency
Allow replicas to temporarily disagree while guaranteeing they converge later.
Bloom Filter
Quickly test whether an item is definitely absent or maybe present.