Databases flashcards, generated for you.

An organized collection of structured data stored and accessed electronically, designed for efficient retrieval, updating, and management through a Database Management System (DBMS).

Atomicity (all-or-nothing transactions), Consistency (valid state before/after), Isolation (concurrent independence), Durability (persistent after commit). Essential for data reliability and preventing corruption.

SQL uses structured schemas and ACID compliance (relational tables); NoSQL uses flexible schemas and prioritizes scalability/availability (documents, key-value, graphs). Trade-off: consistency vs. horizontal scaling.

Process of organizing relational data into structured forms (1NF, 2NF, 3NF, etc.) to eliminate redundancy, reduce update anomalies, and improve data integrity while increasing query complexity.

Intentionally adding redundancy by combining tables to improve read performance at the cost of write complexity and storage. Used when query speed is critical and data consistency can be managed (e.g., analytics, caching).

Data structure (B-tree, hash) enabling faster lookups (O(log n) instead of O(n)). Trade-off: faster reads, slower writes (index must be updated), and increased storage overhead.

Sharding partitions data horizontally across servers by key (load distribution, write scalability). Replication copies full data across servers (read scalability, availability). Can use both together.

Distributed systems can guarantee at most 2 of 3: Consistency (all nodes see same data), Availability (always responsive), Partition tolerance (survives network splits). Most real systems choose AP or CP based on use case.

Guarantee that all replicas converge to same state eventually, but not immediately. Acceptable for non-critical reads (social media, analytics); unacceptable for financial or payment systems requiring strong consistency.

Pooling reuses persistent connections (lower overhead, better concurrency, higher throughput); per-query creates new connection each time (simpler, resource-intensive, higher latency). Pooling is standard for production systems.