When working with Azure Synapse Database and SQL Database Hyperscale, it’s essential to adhere to standard practices and guidelines to ensure optimal performance, security, and maintainability. Here are some best practices for handling objects in both databases:

Azure Synapse Database:

  1. Tables: Design tables with proper schema and data types to minimize storage and improve query performance. Use columnstore indexes for large tables to enhance analytical queries.
  2. Distributions: Choose appropriate distribution keys for distributed tables to evenly distribute data across nodes, preventing hotspots and improving query performance.
  3. Partitions: Implement table partitioning for large tables to enhance data management, improve data loading, and optimize query performance.
  4. Views: Create views to abstract complex queries and simplify data access. Utilize materialized views for improved performance in repetitive queries.
  5. Stored Procedures: Use stored procedures to encapsulate business logic and improve code organization and execution efficiency.
  6. Security: Implement role-based access control (RBAC) to manage user access and permissions effectively. Utilize Azure Active Directory for authentication.
  7. Data Loading: For large-scale data loading, use dedicated data loading mechanisms like PolyBase or COPY command for bulk loading data efficiently.
  8. Monitoring: Regularly monitor database performance using Azure Monitor and set up alerts for critical metrics to respond proactively to issues.

SQL Database Hyperscale:

  1. Data Tiering: Leverage the Hyperscale architecture’s capability to tier data between memory-optimized and disk-based storage to optimize performance and cost.
  2. Automatic Scaling: Utilize the automatic scaling feature to handle sudden spikes in workload and automatically adjust resources based on demand.
  3. Backup and Restore: Implement a backup and restore strategy to ensure data resilience and recovery in case of any failures.
  4. Indexing: Create appropriate indexes to optimize query performance. Hyperscale supports non-clustered columnstore indexes for analytical queries.
  5. Compatibility Level: Keep the compatibility level up-to-date to benefit from the latest performance improvements and features.
  6. Resource Utilization: Monitor and manage resource utilization to avoid overspending and optimize performance.
  7. Database Copy: Use read-only database copies for reporting and analytics to offload read workloads from the primary database.

Remember that these guidelines may change over time due to updates in the services, so it’s crucial to keep up to date with the latest documentation and best practices from Microsoft Azure. Always test any changes in a non-production environment before implementing them in production.