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Retention policies help manage how long data is kept in databases.

Transactions ensure database operations are reliable using ACID properties.

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

OLTP handles transactions while OLAP is for data analysis and reporting.

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

Optimistic and pessimistic locking are strategies to manage database access during concurrent transactions.

Time-based partitioning organizes time-series data into smaller, efficient segments for better querying.

Write-Ahead Log ensures data is safely recorded before changes are made.

Backup strategies include Full, Incremental, and Differential, each with unique benefits.

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

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

Point-in-Time Recovery allows databases to be restored to a specific moment before data loss.

Composite indexes speed up database queries that filter or sort by multiple columns.