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The choice between SQL and NoSQL databases depends on your application's specific needs.

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

Transactions ensure database operations are reliable using ACID properties.

Database isolation levels determine how transactions interact and affect data consistency.

Choosing between a shared database and a database per service affects system design significantly.

Stemming and normalization help search engines match various word forms for better results.

Sharding splits databases into smaller parts to improve performance and scalability.

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

REST API design focuses on creating clean, efficient, and scalable web services.

Database replication helps keep data available and allows systems to handle more read requests.

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

Scaling databases involves deciding whether to enhance read or write capabilities based on traffic patterns.

B-Trees help databases find data quickly without scanning every row.

FAANG engineers use high-level design principles to create scalable systems.

Database indexing speeds up data retrieval by allowing quick lookups.

Load balancers distribute traffic across multiple servers to enhance performance and reliability.

Partition pruning helps databases skip unnecessary data scans, speeding up queries.

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

Protobuf schema evolution requires careful changes to avoid breaking existing clients.