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Replication

As explained in ScyllaDB in Action

Replication is the maintenance of copies of data on multiple nodes.

Replication maintains multiple copies of data across nodes. If one node is unavailable, other holders can answer requests, while the returning node can catch up on missed changes. section 1.1.1

Replication also distributes data ownership as a cluster grows. Adding a node lets the system assign it some existing data slices rather than relying on a single machine. section 1.1.1 section 1.4

The number of replicas required to respond creates a practical trade-off:

  • Require every holder for the most up-to-date result, accepting more internal coordination. section 1.1.1
  • Require one holder for immediate availability, accepting that the answer may not be the newest. section 1.1.1
  • Require two of three holders to tolerate one loss while favoring a recent result. section 1.1.1
Figure 1.5 ABC Data’s approach gives you control over availability and correctness.
figure

Use the figure to compare how replica-response requirements change the balance between availability and correctness. section 1.1.1

How ScyllaDB in Action covers it

How deep it goes
Explains replica ownership, response thresholds, node loss, and recovery, but stops short of implementation mechanics.
Examples
Uses replicated customer-data slices and one-, two-, or three-holder responses to illustrate operational trade-offs.
What you can do after
Evaluate replication choices by balancing response freshness, availability, internal coordination, and tolerance for node loss.
How it connects
Connects replication with availability, consistency, partition tolerance, horizontal scalability, and eventual consistency.

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This explainer was generated by Manning's knowledge graph from the text of ScyllaDB in Action. The section links point to the parts of the book it draws on.