Replication
Replication keeps copies of data on several machines so the system survives failures and serves requests faster.
At a glance
Key signals
0% cross fields · reaches 0 more
- Distributed Systems
- Computer Science
- Explanation
- Examples
- Misconception
- Sourced relations
- Attribution
Dependencies
What this concept builds on and what it makes possible — derived from the atlas’s dependency, causal and structural relations, not from every related edge.
Foundations · builds on
Consensus algorithmenablesReplicationEstablished
Consensus keeps replicas consistent.
Mechanism: A consensus protocol (e.g. Paxos, Raft) makes replicas agree on the same ordered log of updates, so a replicated state machine stays consistent despite failures.
Enables · leads to
ReplicationenablesDistributed computingEstablished
Replication makes systems fault-tolerant.
Mechanism: Keeping copies on several machines means one can fail without losing data or stopping service.
ReplicationcausesEventual ConsistencyEstablished
Replication causes Eventual Consistency.
ReplicationenablesFault ToleranceEstablished
Replication enables Fault Tolerance.
Mechanism: Holding copies on several nodes lets the system serve data even when some replicas fail.
Structural role & consequence
Interpreted from the current atlas graph — what the connections mean, not just how many there are.
Directly enables 3 concepts; following enables/causes relations, 3 concepts are downstream across 2 disciplines.
structural · Follows only enables/causes dependency edges — not general relatedness.
Currently dark in the atlas: no key date stored · 7 of 7 of its relations lack claim-level evidence.
atlas representation · Describes the current Thinking OS representation, not the state of the world.
Builds on 1 foundation (requires / depends-on / derived-from / emerges-from).
structural · Structural graph analysis — not a claim of importance, causation or history.
Structural neighbourhood: 7 → 11 → 15 concepts reachable within 3 hops.
structural · Structural reach — being reachable is not the same as being understood.
cross-field
7 within-field, 0 cross-field
Strengths & constraints
Constraints
- Evidence coverage currently thin in the atlas — few of its relationships carry claim-level evidence. atlas representation
- No dated history stored — the atlas records no key date for this concept. atlas representation
Conditions
- Its dependency reading rests on 1 foundation relation. structural
- Read structurally — most of its relationships carry no external evidence yet, so claims here are graph-derived. structural
Dependency radial
What this concept builds on (left) and what it makes possible (right) — derived from dependency and causal relations.
Seen through each discipline
How this concept sits in each of its fields — derived from its real connections in the graph, not asserted.
Through this lens it connects to CAP theorem, Fault Tolerance, Eventual Consistency and Consensus algorithm.
Through this lens it connects to CAP theorem, Distributed computing and Consensus algorithm.
Related ideas to explore
Concepts that look related but are not yet connected here — candidates for a connection to reason about, not established links.
This idea also appears in…
The same structure shows up in other disciplines. These are real recurrences drawn from the graph — a starting point for asking “what carries over, and what changes?”
Concepts
explicitly analogous
- Connects 7 other ideas across 2 disciplines.
- A local hub: unusually many ideas converge here.
- Most of its connections are of the “Cause & effect” kind.
Derived from the graph’s real structure — observations, not a score.
Sources
- Replication of Objects verified
- Replication of Data verified