Results for “postgresql”

Use this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. **Trigger when user asks to:** - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets **Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.

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Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features

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SQL database migrations with zero-downtime strategies for PostgreSQL, MySQL, SQL Server

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CloudBase PostgreSQL access-pattern and slow-query quality guidance. Use when designing how tables are read and written, eliminating per-row database calls, adding indexes for filters or joins, reviewing high-traffic data access, or explaining a slow SQL query. Not for first-time PG SDK setup, login UI, or NoSQL collections.

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[Deprecated] This is the required documentation for agents operating on the CloudBase Relational Database through MCP. It defines the canonical SQL management flow with `queryMysqlDatabase`, `manageMysqlDatabase`, `queryPermissions`, and `managePermissions`, including destroy flow, async status checks, safe query execution, schema initialization, and permission updates. MySQL provisioning is no longer available through MCP; new environments should use PostgreSQL — see postgresql-development skill instead.

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[Deprecated] Use when building frontend Web apps that talk to CloudBase Relational Database via @cloudbase/js-sdk – provides the canonical init pattern so you can then use Supabase-style queries from the browser. New environments should use PostgreSQL with app.rdb() — see postgresql-development skill instead.

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Use CloudBase document database Web SDK only for confirmed NoSQL collection work. Query, create, update, and delete document data; if the task mentions PostgreSQL / CloudBase PG / app.rdb(), route to postgresql-development instead.

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Use when building, debugging, or evaluating CloudBase PostgreSQL / CloudBase PG / PG mode apps, including Postgres schema setup, queryPgDatabase/managePgDatabase, JS SDK v3 app.rdb() CRUD/RPC, PG HTTP API fallback, RLS-style permissions, username-password auth, and Web CMS/admin CRUD flows backed by CloudBase PG.

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Expert knowledge for Azure Database for MySQL development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when planning MySQL Flexible Server tiers, HA/DR, automated deployments, backups/replication, or secure app connectivity, and other Azure Database for MySQL related development tasks. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines), Azure Database for PostgreSQL (use azure-database-postgresql).

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Enforce multi-tenant isolation and PostgreSQL Row Level Security in NestJS. Use when enforcing tenant isolation or PostgreSQL RLS in NestJS multi-tenant apps.

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用于火山引擎（Volcengine）数据库（MySQL、veDB-MySQL、PostgreSQL、SQL Server、MongoDB、Redis）和公网自建数据库（MySQL和PostgreSQL系列）的元数据管理、数据分析、开发变更、运维诊断、巡检。覆盖实例列表查询、实例下数据库列表查询、表列表查询、表结构查询、数据查询、数据分析与可视化报告（含跨数据源/文件联合分析）、数据治理（资产盘点/数据画像/数据质量/敏感数据识别）、慢查询诊断、死锁与锁等待分析、事务与活跃会话排查、错误日志查询、表空间分析、健康巡检、监控指标查询、变更工单申请等场景。不支持字节云（ByteCloud）数据库，如 ByteRDS / ByteDoc / ByteRedis。

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Execute read-only SQL queries against multiple PostgreSQL databases. Use when: (1) querying PostgreSQL databases, (2) exploring database schemas/tables, (3) running SELECT queries for data analysis, (4) checking database contents. Supports multiple database connections with descriptions for intelligent auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.

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Consult PostgreSQL's parser and grammar (gram.y) to understand SQL syntax, DDL statement structure, and parsing rules when implementing pgschema features

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Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features

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Database specialist covering PostgreSQL, MongoDB, Redis, and advanced data patterns for modern applications

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Optimize slow PostgreSQL inserts in Python using psycopg2. Use when: (1) Row-by-row inserts are taking too long over network, (2) executemany() isn't providing speedup, (3) Migrating large datasets to PostgreSQL, (4) Network latency making individual INSERT statements impractical. The key is using execute_values() from psycopg2.extras instead of executemany() or individual execute() calls.

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Fix PostgreSQL deadlock errors caused by concurrent schema initialization in worker processes. Use when: (1) psycopg2.errors.DeadlockDetected during CREATE INDEX/TABLE IF NOT EXISTS, (2) Multiple Cloud Run jobs, Kubernetes pods, or worker processes start simultaneously, (3) Error shows "Process X waits for RowExclusiveLock... blocked by process Y", (4) init_schema() or migration code runs at worker startup. The key insight: "IF NOT EXISTS" is NOT truly concurrent-safe - PostgreSQL still acquires locks that can deadlock.

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Execute read-only SQL queries against multiple PostgreSQL databases. Use when: (1) querying PostgreSQL databases, (2) exploring database schemas/tables, (3) running SELECT queries for data analysis, (4) checking database contents. Supports multiple database connections with descriptions for intelligent auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.

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Sets up automated database backup, restore, and disaster recovery procedures for PostgreSQL, MySQL, MongoDB, and Redis. Use when you need to implement backup schedules, point-in-time recovery, cross-region replication, backup verification, or disaster recovery runbooks. Trigger words: database backup, pg_dump, mysqldump, mongodump, disaster recovery, point-in-time recovery, WAL archiving, backup rotation, restore database, RTO, RPO, backup verification.

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Manage Amazon RDS for fully managed relational databases. Provision MySQL, PostgreSQL, and Aurora instances with automated backups and patching. Configure read replicas for scaling, snapshots for recovery, and Aurora Serverless for variable workloads.

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Graphile Worker expert for high-performance PostgreSQL job queues with trigger-based job creation and millisecond job pickup via LISTEN/NOTIFY. Use when "graphile worker, postgres trigger job, listen notify queue, postgraphile worker, database trigger queue, transactional job, graphile-worker, postgresql, triggers, listen-notify, job-queue, postgraphile, high-performance, supabase" mentioned.

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Design and implement multi-tenant SaaS architectures with RLS, tenant isolation, and PostgreSQL / Desain dan implementasikan arsitektur SaaS multi-tenant dengan RLS, isolasi tenant, dan PostgreSQL.

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PostgreSQL database design best practices, naming conventions, indexing strategies, and performance optimization for .NET applications using Npgsql and EF Core.

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Apply PostgreSQL schema, migration, and query patterns with idempotent SQL. Use when writing database schemas or migrations.

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