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Database bottlenecks slow down performance, but identifying them helps optimize and scale effectively.

Database per Service ensures each microservice owns its data, reducing dependencies.

The Transactional Outbox Pattern ensures database updates and event publishing are synchronized to avoid losing events.

Database replication enhances data availability and read performance but has challenges like replication lag.

Cache penetration occurs when requests for non-existent data overload the database.

Choose Elasticsearch for complex text searches, but use databases for structured queries.

Distributed locks ensure only one server performs a task, avoiding duplication.

Caching helps applications respond faster by serving data from memory instead of hitting the database.

Cache breakdowns can overwhelm databases, but request coalescing solves this issue.

The USE Method helps find and analyze infrastructure bottlenecks in software systems.