Basic database setups fail when engineers force a single engine to handle every access pattern. Expecting one database to process strict financial transactions, record high-write streaming events, and run complex search queries simultaneously leads to performance bottlenecks and operational failure.
Never force a single database to solve every problem. Instead, adopt Polyglot Persistence - pairing distinct data types with specialized storage engines built for that exact workload. At companies like Netflix, payment records live in MySQL for strict ACID guarantees, high-frequency playback telemetry streams into write-heavy Cassandra, search features run on Elasticsearch, and home feeds serve from EVCache. However, this specialization brings steep operational costs: data duplication across layers, eventual consistency lags, and increased network latency across multiple storage hops.
Polyglot persistence unlocks massive scale by matching access patterns with purpose-built engines, but it is an evolutionary destination for mature systems, not a starting point for early-stage architecture.
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