Results for “suiteql”

Optimize SQL queries, indexes, and database performance across MySQL, PostgreSQL, SQL Server, and Oracle with execution plan analysis and universal tuning techniques.

Kysely type-safe SQL query builder - End-to-end type safety from schema to queries, migrations, transactions, plugins

Guidelines for developing with Kysely, a type-safe TypeScript SQL query builder with autocompletion support

Maps the Salesforce CPQ managed-package object graph (SBQQ__ namespace) and explains when to use the CPQ Quote API for programmatic writes instead of direct DML.

Analiza datos en bases de datos relacionales con consultas SQL eficientes y legibles, incluyendo joins, window functions, CTEs y subqueries, para extraer insights directamente de la base de datos.

SQL injection occurs when untrusted user input is interpolated directly into database queries, allowing attackers to alter query logic. Detect via single-quote errors, boolean-based blind responses (AND 1=1 vs AND 1=2), time-delay payloads (SLEEP, WAITFOR), UNION column enumeration, and error messages from MySQL, Oracle, MSSQL, PostgreSQL. Tools: sqlmap, sqlbftools, Burp Suite, wfuzz with SQLi fuzz strings.

Optimizes SQL queries with execution plan analysis, index suggestions, and query rewriting

Write and debug SOQL queries covering SELECT syntax, filters, sorting, pagination, relationship traversal, and aggregate functions.

Provides PostgreSQL query patterns covering SELECT, JOINs, subqueries, CTEs, window functions, and advanced SQL techniques.

SQL patterns for database querying and design

Analyze SQLite databases using the better-sqlite3 Node.js library, including querying, inserting, and iterating over rows.

Write SOQL queries that group or filter records by date periods using the 13 SOQL date functions, with rules for WHERE vs GROUP BY placement, date-literal comparisons, and fiscal-year restrictions.

Use when the user asks to write SQL queries, optimize database performance, generate migrations, explore database schemas, or work with ORMs like Prisma, Drizzle, TypeORM, or SQLAlchemy.

Connect to PostgreSQL, MySQL, SQLite, and SQL Server databases using SQLAlchemy, Pandas, and DuckDB. Read and write tables, manage sessions, and handle connection strings securely.

Runs SQL queries and data conversions on CSV, Parquet, and JSON files using the DuckDB command-line interface, including schema inspection and output formatting.

Explains syntax differences for common SQL operations across PostgreSQL, MySQL, SQL Server, and Oracle, including auto-increment keys, string concatenation, date functions, pagination, booleans, JSON, case sensitivity, and recursive CTEs.

Use when implementing SQL functionality with production-grade patterns and safeguards.

Translates natural language data intents into syntactically valid Perfetto SQL queries and executes them against a local trace file using trace_processor.

Provides code samples and best practices for using the Azure Tables SDK for Python to perform NoSQL key-value storage, entity CRUD, batch operations, and queries against Azure Storage Tables or Cosmos DB Table API.

Write correct, efficient Kusto Query Language queries with coverage of syntax, joins, dynamic types, datetime pitfalls, regex, serialization, memory management, and advanced functions.

Manages and analyzes Azure SQL databases via Azure CLI, covering DTU/vCore performance, elastic pools, geo-replication, and health monitoring.

SQL with dbt. SQL queries.

Optimizes SQL queries by analyzing execution plans, rewriting patterns, and applying performance techniques for PostgreSQL and MySQL.

Foundational SQL patterns for query writing, schema design, and dialect differences. Use when writing SQL queries, designing database schemas, understanding SQL syntax across PostgreSQL/MySQL/SQLite, or preparing SQL for conversion to other query languages. This is a meta-skill for SQL derivatives.

Enforces SQL quality gates after every implementation: lint with SQLFluff, validate migrations with Flyway or Liquibase, and run database tests with pgTAP or equivalents.

Optimizes SQL queries, designs database schemas, and troubleshoots performance issues using execution plan analysis, indexing strategies, and set-based operations.

Translate natural language into SQL queries, optimize database performance, generate migrations, explore schemas, and work with ORMs across PostgreSQL, MySQL, SQLite, and SQL Server.

Drizzle Raw SQL

Microsoft SQL Server T-SQL procedural language. Covers stored procedures, functions, triggers, error handling, and SQL Server-specific features. Use for SQL Server database server-side programming. USE WHEN: user mentions "tsql", "T-SQL", "SQL Server procedures", "SQL Server functions", "TRY...CATCH", "THROW", "sp_executesql", "SSMS" DO NOT USE FOR: basic SQL Server SQL - use `sqlserver` instead, PostgreSQL - use `plpgsql` instead, Oracle - use `plsql` instead

Use DuckDB from MATLAB via Database Toolbox (R2026a+) as a non-math operations engine on large tabular files (CSV/Parquet/JSON) and as a zero-config embedded database. Use when connecting to DuckDB, querying CSV, Parquet, and JSON files directly with SQL, reducing or profiling large data before MATLAB analysis, creating portable development databases, or installing DuckDB extensions. Triggers on: DuckDB, duckdb(), large CSV/Parquet/JSON, file too large for readtable, filter/aggregate at source, deduplicate, reduce before analysis, profile large file, persistent file import, analytical engine, SQL on CSV, SQL on Parquet, SQL on JSON, query CSV with SQL, query Parquet with SQL, run SQL on files, SQL queries on files, query files directly, SQL without database, in-process SQL.

Use when implementing SQL functionality with production-grade patterns and safeguards.

Oracle Database guidance for SQL, PL/SQL, SQLcl, ORDS, administration, app development, performance, security, migrations, and agent-safe database workflows. Use when the user asks to write, edit, rewrite, review, format, debug, tune, or explain SQL; create or refactor PL/SQL; use SQLcl, Liquibase, ORDS, JDBC, node-oracledb, Python, Java, .NET, or database frameworks; troubleshoot queries, sessions, locks, waits, indexes, optimizer plans, AWR, ASH, migrations, schemas, users, roles, privileges, backup, recovery, Data Guard, RAC, multitenant, containers, monitoring, auditing, encryption, VPD, or safe agent database operations.

dbt (data build tool) transforms data in your warehouse using SQL SELECT statements. Learn project setup, models, tests, documentation, incremental materializations, and integration with data warehouses like PostgreSQL, BigQuery, and Snowflake.

Quick reference for PostgreSQL best practices covering indexing, schema design, query optimization, and security defaults.

Always start with EXPLAIN ANALYZE to understand execution: