Design Microservices Architecture with Patterns and Principles - Adapt: Microservices Architecture with Database Shardin

The video tutorial discusses the implementation of database sharding in an e-commerce architecture, focusing on microservices' data management patterns. It explores NoSQL databases like Cassandra, MongoDB, and Redis, highlighting Cassandra's scalability and availability. Serverless options such as Amazon DynamoDB and Azure Cosmos DB are also considered. The tutorial emphasizes horizontal data partitioning and the benefits of using Cassandra, including its elastic scalability and eventual consistency. The video concludes by encouraging adaptability in technology stacks to meet project requirements.

Which of the following databases is NOT mentioned as an option for implementing database sharding?

• MongoDB

• MySQL

• Redis

• Cassandra

What are the serverless options mentioned for applying the database sharding pattern?

• Amazon DynamoDB and Azure Cosmos DB

• Oracle Cloud and IBM Cloudant

• SAP HANA and Teradata

• Google Bigtable and Firebase

Which part of the architecture remains unchanged when implementing database sharding?

• Distributed databases

• Data partitioning

• Front-end single page applications

• Order microservices

What is a key advantage of using Apache Cassandra for database sharding?

• Simple setup

• Low latency

• High scalability and availability

• Strong consistency

According to the CAP theorem, what is sacrificed when using Cassandra in a microservices architecture?

• Strong consistency

• Partition tolerance

• Eventual consistency

• Availability