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A comprehensive guide for working with Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. This skill covers full lifecycle development, including schema management, data migration (e.g., MySQL to DSQL), multi-tenant patterns, IAM authentication, and advanced query plan explainability. Essential for building robust, scalable applications.

A comprehensive guide for developing and managing applications using Amazon Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. This skill covers core capabilities including direct query execution, robust schema management, safe data migration from MySQL, multi-tenant architectural patterns, IAM-based authentication, and detailed query plan explainability for performance tuning. Essential for developers handling complex database evolution.

Builds a robust, automated workflow to export critical sales data—including forecasts, quota details, adjustments, and CRM totals—from Clari CRM to a designated data warehouse. The pipeline supports multiple targets like Snowflake, BigQuery, and PostgreSQL, ensuring that real-time revenue intelligence is available for advanced analytics and business reporting.

This skill provides expert guidance on building and maintaining applications using Amazon Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. It covers critical areas including schema management, multi-tenant architecture, IAM authentication, and safe data migrations (e.g., MySQL to DSQL). Users can execute direct queries, analyze performance bottlenecks using query plan explainability, and adhere to industry best practices for robust, scalable database design.

This skill provides comprehensive guidance for building and managing applications using Amazon Aurora DSQL, a serverless, distributed, PostgreSQL-compatible SQL database. Topics cover schema management, multi-tenant isolation, IAM authentication, complex DDL migrations (column, constraint), MySQL data type mapping, and advanced query performance tuning using plan explainability tools, ensuring robust and scalable data architecture.

A comprehensive guide to advanced SQL injection (SQLi) methodologies for offensive security assessments and bug bounty hunting. Covers all major injection types, including error-based, boolean/time-based blind, out-of-band, and second-order injection. Provides specific payloads and techniques for MySQL, MSSQL, PostgreSQL, Oracle, and NoSQL databases, along with methods for bypassing WAFs, exploiting GraphQL, WebSocket, and modern API filters. Includes full automation workflows using tools like sqlmap.

A comprehensive and advanced playbook for mastering SQL injection techniques. It covers critical areas including WAF bypass, out-of-band data exfiltration, second-order injection, and exploitation strategies across major database systems (MySQL, MSSQL, Oracle, PostgreSQL). Essential for professional penetration testing and security auditing.

This skill is a comprehensive tool for managing and understanding SQL queries. It can explain complex SQL in plain English for non-technical stakeholders, optimize slow queries by identifying performance bottlenecks, generate functional SQL code from natural language prompts, and produce detailed query documentation and data dictionaries. Supports major dialects including PostgreSQL, MySQL, and BigQuery.

This comprehensive guide serves as a detailed reference for psql, the feature-rich interactive terminal for PostgreSQL. It covers connection methods (CLI flags, environment variables, ~/.pgpass), executing SQL queries, inspecting database objects using commands like \d, and managing data operations such as importing and exporting.

A comprehensive guide to safe and reversible database migration patterns. Covers zero-downtime schema changes, data backfilling, and rollbacks for major databases like PostgreSQL and MySQL, and popular ORMs (Prisma, Drizzle, Django). Learn techniques like concurrent indexing and the expand-contract pattern to ensure production stability.

A comprehensive guide to PostgreSQL best practices, covering advanced indexing (GIN, BRIN, Partial), schema design, performance tuning, and security implementation (RLS). It details optimizing common SQL patterns like cursor pagination and UPSERT, essential for building high-performance, reliable database systems.

This comprehensive guide teaches researchers how to conduct an exhaustive "reinvention audit" for academic papers, specifically in the database field. It covers searching deep historical literature (pre-2000), modern conference venues (SIGMOD, ICDE), and industrial open-source systems (PostgreSQL, RocksDB) to ensure true novelty and properly position the contribution delta.