Consult PostgreSQL's pg_dump implementation for guidance on system catalog queries and schema extraction when implementing pgschema features
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Consult PostgreSQL's pg_dump implementation for guidance on system catalog queries and schema extraction when implementing pgschema features
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Comprehensive guide to PostgreSQL migrations - common errors, generated columns, full-text search, indexes, idempotent migrations, and best practices for database schema changes
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Comprehensive guide for migrating PostgreSQL tables to TimescaleDB hypertables with optimal configuration and performance validation
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Analyze an existing PostgreSQL database to identify tables that would benefit from conversion to TimescaleDB hypertables
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Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.
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Expert guide for Backend.AI distributed computing platform. Automatically activates when users ask about: - Backend.AI architecture, components (Manager, Agent, Storage Proxy, Webserver, App Proxy) - Features (session scheduling, Sokovan orchestrator, multi-tenancy, resource allocation) - APIs (REST, GraphQL), authentication, RBAC authorization - Container runtime (kernels, jail sandbox, hook library, virtual folders) - Accelerator support (CUDA, ROCm, TPU, NPU, Graphcore IPU) - Client SDKs (Python, Java, JavaScript, PHP) - Setup, requirements (Python 3.13+, Docker, PostgreSQL, Redis, etcd) - How WebUI connects to/interacts with Backend.AI backend - Plugin interfaces, development setup, infrastructure Use when user mentions "Backend.AI", "backend.ai", "Sokovan", component names, or asks about the backend platform this WebUI connects to. allowed-tools: WebFetch, Read
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Comprehensive backend development guide for Langfuse's Next.js 14/tRPC/Express/TypeScript monorepo. Use when creating tRPC routers, public API endpoints, BullMQ queue processors, services, or working with tRPC procedures, Next.js API routes, Prisma database access, ClickHouse analytics queries, Redis queues, OpenTelemetry instrumentation, Zod v4 validation, env.mjs configuration, tenant isolation patterns, or async patterns. Covers layered architecture (tRPC procedures → services, queue processors → services), dual database system (PostgreSQL + ClickHouse), projectId filtering for multi-tenant isolation, traceException error handling, observability patterns, and testing strategies (Jest for web, vitest for worker).
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Provides AWS CloudFormation patterns for Amazon RDS databases. Use when creating RDS instances (MySQL, PostgreSQL, Aurora), DB clusters, multi-AZ deployments, parameter groups, subnet groups, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.
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Provides Better Auth integration patterns for NestJS backend and Next.js frontend with Drizzle ORM and PostgreSQL. Use when setting up Better Auth with NestJS backend, integrating Next.js App Router frontend, configuring Drizzle ORM schema, implementing social login (GitHub, Google), adding plugins (2FA, Organization, SSO, Magic Link, Passkey), implementing email/password authentication with session management, or creating protected routes and middleware.
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Provides comprehensive Drizzle ORM patterns for schema definition, CRUD operations, relations, queries, transactions, and migrations. Proactively use for any Drizzle ORM development including defining database schemas, writing type-safe queries, implementing relations, managing transactions, and setting up migrations with Drizzle Kit. Supports PostgreSQL, MySQL, SQLite, MSSQL, and CockroachDB.
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Provides patterns to configure AWS RDS (Aurora, MySQL, PostgreSQL) with Spring Boot applications. Configures HikariCP connection pools, implements read/write splitting, sets up IAM database authentication, enables SSL connections, and integrates with AWS Secrets Manager. Use when setting up RDS connections in Spring Boot, configuring connection pooling, or managing database credentials securely.
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Provides configuration patterns for LangChain4J vector stores in RAG applications. Use when building semantic search, integrating vector databases (PostgreSQL/pgvector, Pinecone, MongoDB, Milvus, Neo4j), implementing embedding storage/retrieval, setting up hybrid search, or optimizing vector database performance for production AI applications.
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Creates and scaffolds a new Spring Boot project (3.x or 4.x) by downloading from Spring Initializr, generating package structure (DDD or Layered architecture), configuring JPA, SpringDoc OpenAPI, and Docker Compose services (PostgreSQL, Redis, MongoDB). Use when creating a new Java Spring Boot project from scratch, bootstrapping a microservice, or initializing a backend application.
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Designs relational and document database schemas from requirements or an existing app - tables and collections, keys, relationships, constraints, indexes driven by real query patterns, ERDs, and reversible migration scripts - with PostgreSQL (including Supabase) as the default and MySQL, SQLite, and MongoDB supported. Use when the user wants to model data for a new app or feature, review or fix an existing schema, choose keys or indexes, plan multi-tenancy, normalize or denormalize, or write CREATE TABLE statements or migrations, even if they just describe their app and ask "how should I store this". For moving data between database providers, use database-migrator.
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Build managed ingestion pipelines into Databricks using Lakeflow Connect. Use when ingesting from SaaS apps (Salesforce, Workday Reports, ServiceNow, Google Analytics 4, HubSpot, Confluence) or databases (SQL Server cloud and on-prem; PostgreSQL/MySQL CDC in PuPr) into Unity Catalog with serverless pipelines.
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Use when designing PostgreSQL + Redis data models, indexes, caching strategies, JSONB usage, tiered storage, or cache consistency contracts.
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Fix Node.js pg-pool not reconnecting after CloudSQL connection reset (ECONNRESET). Use when: (1) Retries fail with same ECONNRESET error despite retry logic, (2) "Connection terminated" or "connection already closed" errors persist across retries, (3) "remaining connection slots are reserved" errors in CloudSQL, (4) High-concurrency Node.js app with pg-pool and CloudSQL/managed PostgreSQL. The pool caches dead connections - you must recreate the pool, not just retry.
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Fix psycopg2 "could not receive data from server: Operation timed out" or "connection already closed" errors when using Cloud SQL with long-running Python scripts. Use when: (1) psycopg2.OperationalError after a period of no DB activity, (2) DB connection works initially but fails after a non-DB phase (API calls, file processing, CDX scans), (3) Cloud SQL managed PostgreSQL kills idle connections. The fix is to defer DB connection opening until needed, or add reconnection logic for long-running batch processes.
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Write correct, performant SQL across all major data warehouse dialects (Snowflake, BigQuery, Databricks, PostgreSQL, etc.). Use when writing queries, optimizing slow SQL, translating between dialects, or building complex analytical queries with CTEs, window functions, or aggregations.
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Streams change data capture from PostgreSQL into Redpanda or Kafka using Redpanda Connect's postgres_cdc input, which reads the WAL through logical replication (pgoutput). Use when configuring postgres_cdc (formerly pg_stream), setting up wal_level=logical, replication slots, and publications, enabling an initial snapshot before streaming, or troubleshooting slot growth and WAL accumulation. Also covers Redpanda Enterprise destination features such as Iceberg Topics, Tiered Storage, and server-side Schema ID Validation, since postgres_cdc itself requires a Redpanda Enterprise license.
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| Nuxt 4 server-side development with Nitro: API routes, server middleware, database integration, and backend patterns. Use when: creating server API routes, implementing server middleware, integrating databases (D1, PostgreSQL, Drizzle), handling file uploads, implementing WebSockets, or building backend logic with Nitro.
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Cloudflare Hyperdrive for Workers-to-database connections with pooling and caching. Use for PostgreSQL/MySQL, Drizzle/Prisma, or encountering pool errors, TLS issues, connection refused.
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Validate database integrity, test migrations forward and backward, verify schema constraints, manage seed data, detect migration drift, and identify query performance issues. Covers PostgreSQL, MySQL, MongoDB with Prisma, TypeORM, Drizzle, and SQLAlchemy, plus Testcontainers test databases. Use when: "database test," "migration test," "migration rollback," "rollback test," "data integrity," "SQL test," "schema validation," "seed data," "query performance," "Testcontainers." Not for: synthetic data generation/masking at scale — use test-data-management; Docker/IaC test-environment provisioning — use test-environments; SQL injection — use security-testing. Related: test-data-management, test-environments, security-testing, ci-cd-integration.
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Designs database schemas with proper normalization, indexing, constraints, and tenant isolation patterns. Use when someone needs to create a new database schema, add multi-tenant support, design row-level security policies, or optimize table structures. Trigger words: database schema, table design, RLS, row-level security, foreign keys, indexes, migrations, ERD, data model, normalization.
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