- Published on
Learn what ACID stands for in databases — Atomicity, Consistency, Isolation, Durability — with real-world examples to understand how transactions stay reliable and safe.
Databases
All Posts
- system-design (114)
- database (27)
- low-level-design (22)
- oop (15)
databases (15)
- misc (10)
- normalization (9)
- load-balacing (9)
- indexes (8)
- erd (7)
- caching (7)
- networking (7)
- uml (6)
- solid (6)
- messaging (6)
- security (6)
- theorem (6)
- oop-pillars (5)
- data-partitioning (5)
- data-modeling (4)
- functional-dependency (4)
- bloom-filters (4)
- cdn (4)
- dbms (3)
- relational-data-model (3)
- api-gateway (3)
- recovery (3)
- distributed-file-system (3)
- dns (3)
- proxy (3)
- replication (3)
- data-structures (2)
- interview-prep (2)
- relational-model (2)
- oop-principle (2)
- scalability (2)
- check-sum (2)
- redundancy (2)
- key-concepts (1)
- tips (1)
- armstrong-axioms (1)
- integrity-constraints (1)
- er-diagram (1)
- oop-relationship (1)
- concurrency (1)
- high-availability (1)
- availability (1)
- observability (1)
- monitoring (1)
- error-handling (1)
- leader-follower (1)
- architectural-pattern (1)
- load-balacing-algorithms (1)
- load-balacing-uses (1)
- batch-processing (1)
- streams (1)
- heart-beat (1)
- synchronous (1)
- asynchronous (1)
- quorum (1)
- Published on
Compare ACID and BASE database models. Learn key differences, CAP theorem trade-offs, and when to use each in real-world systems like banking, e-commerce, or social media.- Published on
Explore real-world examples of ACID and BASE databases. Learn how MySQL, PostgreSQL, Cassandra, DynamoDB, and others align with different data models, and when to use each.- Published on
Learn what BASE stands for in NoSQL databases — Basically Available, Soft state, Eventually consistent — and how it differs from ACID for distributed systems and high availability.- Published on
Understand the key differences between data replication and data mirroring. Learn when to use each for availability, backup, and disaster recovery. 📊