Cloud-native NoSQL databases prioritize availability and partition tolerance (CAP theorem), implementing eventual consistency to handle distributed system challenges while maintaining horizontal scalability.
Data warehouses use materialized views to pre-aggregate data and strategic denormalization for faster analytical queries. These techniques significantly improve performance on large fact tables.
B+ Tree indexes maintain sorted order and support efficient range queries, point queries, and prefix searches. Hash indexes are faster for exact matches but cannot handle range queries efficiently.
Supervised learning trains on labeled data (features + targets); unsupervised finds patterns in unlabeled data without predefined outputs.
SQL injection exploits vulnerable input handling to execute unintended SQL commands, potentially exposing or modifying data.
Normalization scales features (e.g., 0-1 range) preventing features with larger scales from dominating model training.
Dijkstra's algorithm efficiently finds shortest paths from a source node to all other nodes in weighted graphs with non-negative weights.
TRUNCATE is DDL (immediate, cannot be rolled back in most databases), DELETE is DML (slower, can be rolled back).
PaaS (Platform as a Service) provides a platform to develop and deploy applications without managing underlying infrastructure.
Quicksort's worst-case complexity is O(n²) when pivot selection is poor, though average case is O(n log n).