'postgres' 검색 결과

dlt (data load tool) is an open-source Python library that loads data from APIs, files and databases into warehouses and lakes, inferring the schema and tracking incremental state for you. Use when a user asks to build a data pipeline in Python, load a REST API into DuckDB, BigQuery, Snowflake or Postgres, set up incremental or merge loading, enforce a schema contract, or replace a hand-written ETL script or a hosted ELT connector.

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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.

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Plans and scripts data migrations between SQL databases: schema mapping, type conversion, batched and resumable loading, validation and cutover. Use when the user mentions "data migration," "database migration," "migrate from MySQL to PostgreSQL," "schema migration," "ETL pipeline," "data transfer," "database consolidation," "legacy migration," or "move data between databases." Covers schema analysis, mapping, transformation, batch processing, validation, and cutover planning. For query optimization during migration, see sql-optimizer.

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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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Runs background jobs in Node.js with BullMQ, a job queue library backed by Redis (or PostgreSQL since v6): delayed and prioritized jobs, retries with backoff, rate limiting, cron-style job schedulers, parent-child flows and concurrency control. Use when a user asks to add a background worker, queue emails or webhooks, schedule recurring jobs, retry failed jobs, rate limit an API client, or migrate from Bull or from BullMQ 5 repeatable jobs.

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Expert knowledge for Drizzle ORM - the lightweight, type-safe SQL ORM for edge and serverlessUse when "drizzle, drizzle orm, drizzle-kit, drizzle schema, drizzle migration, drizzle relations, sql orm typescript, edge database, d1 database, orm, database, typescript, sql, edge, serverless, d1, postgres, mysql, sqlite" mentioned.

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Database design specialist for schema modeling, query optimization, indexing strategies, and data integrityUse when "database design, schema, indexes, query optimization, migrations, normalization, database scaling, foreign keys, data modeling, database, sql, postgres, mysql, mongodb, schema, indexes, migrations, normalization, optimization" mentioned.

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Expert at evolving database schemas safely. Covers migration strategies, zero-downtime deployments, rollback planning, and data transformation. Knows how to change production schemas without breaking running applications. Use when "database migration, schema change, add column, alter table, drizzle migrate, prisma migrate, zero downtime migration, rollback migration, database, migrations, schema, drizzle, prisma, postgresql, zero-downtime" mentioned.

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World-class database schema design - data modeling, migrations, relationships, and the battle scars from scaling databases that store billions of rowsUse when "database schema, data model, migration, prisma schema, drizzle schema, create table, add column, foreign key, primary key, uuid, auto increment, soft delete, normalization, denormalization, one to many, many to many, junction table, polymorphic, enum type, index strategy, database, schema, migration, data-model, prisma, drizzle, typeorm, postgresql, mysql, sqlite" mentioned.

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World-class backend engineering - distributed systems, database architecture, API design, and the battle scars from scaling systems that handle millions of requestsUse when "backend, api, database, postgres, mysql, mongodb, redis, graphql, rest, authentication, authorization, caching, queue, background job, webhook, migration, transaction, n+1, rate limit, server, node.js, python, go, backend, api, database, architecture, performance, reliability, security" mentioned.

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ALWAYS activate when the user's query involves Docker in any way — even if it also matches other skills. If the words docker, Dockerfile, docker-compose, compose.yml, container, or image appear in the query, this skill MUST be used. Covers: writing or editing Dockerfiles and compose files, adding services (postgres, redis, etc.) to compose, volume mounts and data persistence, docker build failures (layer caching, npm install issues), healthchecks and service startup ordering (depends_on), environment variables in containers, port mapping, container crashes and exit codes (OOM/137), non-root users, multi-stage builds, image optimization, .dockerignore, and deploying to container runtimes. Takes priority over general implementation or debugging skills when Docker infrastructure is the subject.

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Use when writing tests for a TypeScript service on Node.js - Vitest or the repository's Jest / node:test, fakes at port boundaries, HTTP through app.inject or supertest, Testcontainers Postgres for queries, fake timers, test-first

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Use when writing tests for C#/.NET code - xUnit structure, NSubstitute or the repository's mocking library at ports, WebApplicationFactory for HTTP, Testcontainers Postgres for EF Core, FakeTimeProvider, test-first

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Use when tools from the jupyter, duckdb, dbt, mlflow, huggingface or postgres MCP servers appear in your tool list, or before reaching for one — what each is good for, what it can damage, and the CLI fallback when it is not connected

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Use when changing the database schema - detect the repo's migration tool, ship a new migration in its layout, never edit an applied one, and avoid lock-unsafe DDL on a live table

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Use when writing or changing a query against PostgreSQL from Go — avoiding N+1 loops, reading EXPLAIN output, indexing, and keyset pagination

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Use when writing Go tests that need test doubles or cover multiple cases - detect the repo's mocking approach (Mockery v3, gomock, hand-written testify mocks, fakes), table-driven cases, testify suites when the repo uses them, and real-Postgres tests for repository adapters

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PostgreSQL database administration — backup/restore (pg_dump, PITR, WAL archiving), health monitoring (connections, bloat, cache hit ratio, dead tuples), connection pooling (PgBouncer), replication (streaming, logical), vacuum/autovacuum tuning, and scheduled backups with retention. Use when user asks to backup a database, restore from backup, monitor database health, set up replication, or perform DBA tasks. Do NOT use for schema design (use db-sculptor), query optimization (use db-sculptor), or migration planning (use db-sculptor).

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Design database schemas with Prisma/Drizzle, PostgreSQL index strategy (B-tree, GIN, GiST, BRIN, Hash), query optimization (EXPLAIN ANALYZE), migration safety (expand/contract, zero-downtime), and sharding/partitioning. Use when user asks to design schema, create migrations, optimize slow queries, add indexes, choose between SQL/NoSQL, or set up Prisma/Drizzle. Do NOT use for data warehouse dimensional modeling, ETL pipeline design, or non-relational (MongoDB, DynamoDB) schema design.

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Designs database schemas, migrations, and data models for PostgreSQL, MySQL, MongoDB, and Redis. Use when planning tables, relationships, indexes, or ORM-backed schema changes.

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Diagnoses and tunes SQL for OLTP workloads on PostgreSQL, MySQL, and SQL Server. Use when tuning queries, reading plans, indexing, or fixing lock contention.

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Design schemas, write queries for MongoDB and PostgreSQL. Use for database design, SQL/NoSQL queries, aggregation pipelines, indexes, migrations, replication, performance optimization, psql CLI.

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Craft Cloud — Pixel & Tonic's serverless hosting platform for Craft CMS. Covers craft-cloud.yaml configuration, the Build → Migrate → Release deploy pipeline, the craftcms/cloud extension package, edge image transforms via Cloudflare, edge static caching with cache.rules + ESI, Cloud-managed S3 filesystem, MySQL 8 / Postgres 15 databases (no MariaDB, no tablePrefix), Console-based command runner and scheduled cron (once-per-hour minimum), auto-handled queue jobs, custom domains and SSL, preview environments per branch, Cloud limitations (ephemeral filesystem, no SSH, no .htaccess, no built-in mail), plugin development requirements for Cloud compatibility, and self-hosted → Cloud migration.

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Reviews sqlx database code for compile-time query checking, connection pool management, migration patterns, and PostgreSQL-specific usage. Use when reviewing Rust code that uses sqlx, database queries, connection pools, or migrations. Covers offline mode, type mapping, and transaction patterns.

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