I have extensive experience in designing scalable database architectures, having worked on projects that required high availability and performance. I utilize techniques such as sharding, partitioning, and replication to ensure that databases can handle increasing loads without compromising performance. My approach involves thorough capacity planning and performance testing to identify potential bottlenecks and implement solutions that scale horizontally and vertically.

Ensuring data integrity and security is paramount in my database designs. I implement robust validation checks, referential integrity constraints, and transaction management to maintain data accuracy. For security, I employ encryption for sensitive data, role-based access control (RBAC), and regular security audits. I also stay updated with the latest security practices and compliance standards to protect against threats and vulnerabilities.

Optimizing query performance in large databases involves several strategies. I start by analyzing query execution plans to identify slow-running queries and inefficient joins. I then optimize indexing, ensuring that indexes are appropriately created and maintained. Additionally, I use techniques like query caching, materialized views, and denormalization where appropriate to reduce query complexity and improve response times. Regular monitoring and tuning are also essential to maintain optimal performance.

Handling database migrations and upgrades requires careful planning and execution. I begin by creating a detailed migration plan that includes data validation, backup strategies, and rollback procedures. I use tools like ETL processes to migrate data efficiently and minimize downtime. During the upgrade, I ensure compatibility with existing systems and perform thorough testing in a staging environment before deploying to production. Communication with stakeholders is key to managing expectations and mitigating risks.

I have experience working with NoSQL databases such as MongoDB and Cassandra, which offer advantages in scalability and flexibility for unstructured data. NoSQL databases are particularly useful for handling large volumes of data and distributed systems. In contrast, SQL databases are better suited for complex queries and transactions requiring ACID compliance. My approach involves selecting the appropriate database type based on the specific requirements of the project, whether it's scalability, data structure, or transaction integrity.