What problem does it solve?
This skill helps developers and DBAs optimize SQL performance on cloud-native and HTAP databases by identifying bottlenecks, tuning queries, and ensuring scalable data processing across OLTP and OLAP workloads.
Core Features & Use Cases
- Modern database systems and platforms knowledge for cloud-native databases: Amazon Aurora, Google Cloud SQL, Azure SQL Database, Snowflake, Google BigQuery, Amazon Redshift, Databricks, CockroachDB, TiDB, and more.
- Advanced query techniques and optimization: window functions, recursive CTEs, complex joins, plan analysis, and parallel query execution.
- Performance tuning and optimization: indexing strategies, statistics maintenance, partitioning, memory configuration, and I/O considerations.
- Cloud database architecture: multi-region deployment, auto-scaling, backup, disaster recovery, and data migration strategies.
- Data modeling and schema design: normalization vs denormalization, star/snowflake schemas, SCDs, and HTAP schema considerations.
Quick Start
Provide an optimized SQL example suite for a high-traffic OLTP/OLAP workload and explain the rationale behind each improvement.