Category

Database Engineering

SQL, NoSQL, query optimization and data modeling

99 posts

ACID Trade-offs: Balancing Consistency and Availability in Distributed Transactions

In the early days of relational databases, ACID properties—Atomicity, Consistency, Isolation, and Durability—were the gold standard for data integrity. For decades, developers could assume that a transaction was an immutable unit of work. However, as systems scaled horizontally to handle massive ...

Implementing SSPI in High-Throughput PostgreSQL

Choosing the right isolation level in PostgreSQL is often a balancing act between data consistency and system throughput. While READ COMMITTED is the default and offers high performance, it is susceptible to non-repeatable reads and phantom reads. On the other end of the spectrum, the SERIALIZABL...

MVCC Deep Dive: Solving Phantom Reads

Multi-Version Concurrency Control (MVCC) is the backbone of modern transactional databases. While it excels at preventing readers from blocking writers and vice versa, it introduces subtle concurrency anomalies like phantom reads and write skew. For engineers building high-concurrency application...

Scaling with Intelligence: Advanced Redis Patterns Beyond Simple Caching

For many developers, Redis is synonymous with the Cache-Aside pattern: a quick check in the database, a lookup in memory, and a write-through if missed. While effective for simple read-heavy workloads, modern distributed systems demand more from their caching layer. As applications scale, the nee...