Eight Common Software Architecture Design Patterns and Their Pros and Cons

Architecture is the skeleton of software, similar to the human skeleton supporting the body. This article introduces eight common architectural design patterns, explains their typical scenarios, advantages and disadvantages.

1. Single Database Single Application – the simplest pattern with one database and one application; fast development but poor performance, scalability, and high‑availability.

2. Content Distribution – uses CDN and object storage to serve static resources close to users; reduces backend load and bandwidth usage, but adds cost and data‑consistency challenges.

3. Query Separation – separates read/write using master‑slave databases and optionally Elasticsearch; improves read performance and reduces primary DB pressure, yet introduces data latency and consistency issues.

4. Microservices – splits business into independent services communicating via RPC/MQ; enhances scalability, fault isolation, and team autonomy, but increases system complexity, operational overhead, and requires robust monitoring.

5. Multi‑Level Cache – adds caches at client, API gateway, and backend layers; dramatically reduces read latency and backend pressure, while cache invalidation can cause snowball effects.

6. Database Sharding (Split‑Database Split‑Table) – distributes tables across multiple hosts/instances to relieve single‑node pressure; reduces table load and improves write throughput, but makes transactions, joins, and query logic more complex.

7. Elastic Scaling – dynamically adds or removes instances from a resource pool (VM or container) based on metrics; provides on‑demand capacity and cost efficiency, yet requires reliable monitoring, automation, and handling of stateful services.

8. Multi‑Data‑Center – deploys services in multiple geographic regions for high availability and low latency; solves user‑side latency, but brings data synchronization, consistency, and routing challenges.

Overall, the article emphasizes selecting the appropriate pattern according to business needs and avoiding over‑fragmentation, while being aware of each pattern's trade‑offs.