Results for “database”

Expert guidance for Ibis, the Python dataframe library that provides a pandas-like API but generates SQL for execution on any backend — DuckDB, PostgreSQL, BigQuery, Snowflake, Spark, and more. Helps developers write analytics code once and run it anywhere without rewriting SQL for each database.

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.

Discover, classify, and protect sensitive data across cloud storage, databases, and data pipelines using Amazon Macie, Azure Information Protection, and Google Cloud DLP API.

Creates a MariaDB REST Service by configuring the REST metadata schema, creating the service and REST schema, and exposing tables, views, and routines as REST endpoints via SQL DDL in mariadb-shell.

Ingests music into a LanceDB via ncmdump-rs and sf-cli, searching and downloading from Netease Cloud Music or Bilibili, decrypting local NCM files, and extracting metadata, lyrics, and cover art.

Explains MariaDB-specific behavior of DROP USER and RENAME USER, including multiple accounts per statement, IF EXISTS handling, active-connection warnings, and effects on privileges and definers. Use when writing or reviewing account-lifecycle SQL for MariaDB.

Supabase administration, RLS policies, migrations, and schema design. Use for database architecture, Row Level Security, performance tuning, auth integration. Activate on "Supabase", "RLS", "migration", "policy", "schema", "auth.uid()". NOT for Supabase Auth UI configuration (use dashboard), edge functions (use cloudflare-worker-dev), or general SQL without Supabase context.

Explains MariaDB-specific CREATE INDEX and DROP INDEX syntax, including mapping to ALTER TABLE, prefix lengths for TEXT/BLOB, lack of expression indexes, real descending indexes, IGNORED indexes, and index kinds. Use when writing or reviewing index statements for MariaDB.

Scaffold a MariaDB Schema Management (MSM) project and author the initial schema in the development folder, creating the project with msm.create_project and writing the first version's tables, objects, and grants into the MSM sections of <schema>_next.sql.

Diagnose and observe an Oxla distributed analytical database using system catalog tables, Prometheus metrics, runtime log-level changes, and troubleshooting workflows for slow queries, node health, and memory/OOM pressure. Also covers debugging Oxla's external data sources, including the Redpanda/Kafka ingestion path.

Browse and inspect MariaDB REST Service objects using read-only SHOW REST and SHOW CREATE REST statements to list services, schemas, views, procedures, functions, content sets, auth apps, roles, grants, and dump DDL for reverse-engineering or auditing.

Use this skill when the user is working with Supabase and needs help with Edge Functions, SQL schema or migrations, Auth, Row Level Security, database functions, local CLI workflows, or deployment. Use it for building features, reviewing Supabase code, creating migrations, writing policies, implementing auth-aware server logic, and debugging full Supabase app flows.

Comprehensive toolkit for developing with the CocoIndex library. Use when users need to create data transformation pipelines (flows), write custom functions, or operate flows via CLI or API. Covers building ETL workflows for AI data processing, including embedding documents into vector databases, building knowledge graphs, creating search indexes, or processing data streams with incremental updates.

You are an expert in Knex.js, the flexible SQL query builder for Node.js that supports PostgreSQL, MySQL, SQLite, and MSSQL. You help developers write type-safe queries with a chainable API, manage database migrations and seeds, build complex joins and subqueries, and use transactions — providing direct SQL control without the overhead of a full ORM.

Builds and deploys Firebase SQL Connect (aka Firebase Data Connect) backends with PostgreSQL securely. Use when designing schemas with tables and relations, writing authorized queries and mutations, configuring real-time data updates, or generating type-safe SDKs. Use when you need a relational database with Firebase, or when the user mentions SQL Connect or Data Connect.

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.

Oracle PL/SQL procedural language. Covers stored procedures, functions, packages, triggers, cursors, collections, and exception handling. Use for Oracle database server-side programming. USE WHEN: user mentions "plsql", "Oracle procedures", "Oracle packages", "Oracle triggers", "BULK COLLECT", "FORALL", "DBMS_OUTPUT", "Oracle functions" DO NOT USE FOR: basic Oracle SQL - use `oracle` instead, PostgreSQL - use `plpgsql` instead, T-SQL - use `tsql` instead

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 for writing, reviewing, debugging, testing, or optimizing Python code that embeds DuckDB, executes analytical SQL, manages DuckDB connections and transactions, builds DuckDB relations, queries Parquet/CSV/Arrow/pandas/Polars inputs, or exports query results. Trigger on connection scope, parameters, replacement scans, materialization, concurrency, extensions, and query plans. Do not use for generic SQL with another engine, DuckDB CLI-only work, server-database administration, dbt-only projects, or dataframe work that does not call DuckDB.

Design data systems by understanding storage engines, replication, partitioning, transactions, and consistency models. Use when the user mentions "database choice", "replication lag", "partitioning strategy", "consistency vs availability", "stream processing", "ACID transactions", "eventual consistency", or "LSM tree vs B-tree". Also trigger when choosing between SQL and NoSQL, designing data pipelines, or debugging distributed system consistency issues. Covers data models, batch/stream processing, and distributed consensus. For system design, see system-design. For resilience, see release-it.

Structured data + RAG. NL2SQL hybrid patterns (text-to-SQL then execute vs embed rows), table embedding strategies (row-level, schema-level, hybrid), semantic layer integration (Cube, dbt metrics), LangChain SQLDatabaseChain, LlamaIndex PandasQueryEngine, safe SQL execution (read-only, sandboxed), schema-aware retrieval. Full PostgreSQL + pgvector hybrid code. USE WHEN: user mentions "tabular RAG", "NL2SQL", "text to SQL", "RAG on tables", "database RAG", "SQL RAG", "semantic layer", "structured data RAG" DO NOT USE FOR: unstructured doc RAG - use `rag-architecture`; metadata filtering only - use `self-querying-retriever`; KG retrieval - use `graph-rag`