Managing multiple databases in a microservices architecture introduces operational and consistency challenges that don't exist with a single shared database.
Key Points: • Each database needs its own provisioning, backups, monitoring, and upgrades, multiplying operational overhead as the number of services grows. • Keeping data consistent across services becomes harder since there's no single transaction that can span multiple databases. • Data duplication is common, since services often keep local copies of data owned by another service, which risks the copies drifting out of sync. • Cross-service reporting and analytics become more difficult, often requiring a separate data warehouse or CDC pipeline to aggregate data. • Different database technologies per service increase the range of operational skills a team needs, from tuning a relational database to managing a document store.
Example: A reporting team that used to run one SQL join across Orders and Customers now needs a data pipeline that extracts data from both services' databases into a warehouse, since there's no longer a single database to query directly.
Interview Tip: A concise interview answer is:
"The main challenges are operational overhead from running many databases, harder cross-service consistency without shared transactions, and data duplication as services cache each other's data. Teams typically address this with event-driven synchronization, the outbox pattern, and a separate analytics pipeline like CDC into a warehouse for cross-service reporting."