Database Insights

Complete MongoDB guide covering document modeling, aggregation pipelines, sharding, replication, and Atlas deployment. Learn when MongoDB is the right choice for your application.

Explore the trade-offs between database normalization and denormalization for optimal performance. Learn when to normalize for data integrity and when to denormalize for query speed.

Twelve schema design patterns that survive production scale: primary key strategy, normalization trade-offs, partitioning, sharding boundaries, and indexing rules.

Understand RDS Multi-AZ for HA and Read Replicas for read scaling — failover behavior, replication lag, and costs

Use Aurora Serverless v2 for cost-effective scaling — ACU configuration, scaling behavior, and when it fits

Configure Redis Cluster for horizontal scaling — hash slots, replication, failover, and client-side routing

Design MongoDB sharded clusters — choose shard keys, manage chunk balancing, and avoid hot shards in production

Configure pgBouncer correctly for your PostgreSQL workload. Compare transaction vs session pooling, size your pool correctly, and monitor pool health in production.

Right-size your PostgreSQL connection pool using the (cores*2)+1 formula. PgBouncer configuration, per-user limits, pool saturation monitoring, and transaction mode pitfalls.

Enable and tune PostgreSQL parallel query for analytical workloads. Covers max_parallel_workers settings, PARALLEL SAFE functions, JIT compilation, and execution plan verification.

Compare database sharding strategies: hash sharding for even distribution, range sharding for locality, and directory-based for flexibility. When to shard and alternatives.

DynamoDB and MongoDB are the two most common NoSQL choices, but cost structures, query flexibility, and operational overhead differ dramatically depending on your access patterns.