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6.1Distributed databases and replication
Covers horizontal partitioning and vertical partitioning for distributing data across sites, replication (synchronous replication, asynchronous replication) for duplicating data, the six transparencies that realize distribution transparency, sharding for scale-out, and the CAP theorem, BASE, and eventual consistency that describe the limits of distributed systems.
As data volume and access load grow beyond what a single server can handle, distributing a database across multiple sites or nodes becomes an unavoidable design decision. But distribution is not free—there is a constant trade-off among consistency, availability, and response performance, and which to prioritize and which to sacrifice. A database designer or data-platform engineer must be able to select the right partitioning scheme, replication method, and consistency model according to business requirements—whether consistency is paramount (as in financial transactions) or availability and responsiveness take priority (as in a social-media feed). This section builds the pattern for that design judgment on top of how distributed databases actually work.
6.1.1Partitioning data: horizontal and vertical
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