القائمة
Automate database synchronization, replication, migration, and cross-platform data integration
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اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/claude-office-skills/skills --skill database-syncيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
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عرض SKILL.md
| name | Database Sync |
| description | Automate database synchronization, replication, migration, and cross-platform data integration |
| version | 1.0.0 |
| author | Claude Office Skills |
| category | data |
| tags | ["database","sync","replication","migration","integration"] |
| department | engineering |
| models | ["claude-3-opus","claude-3-sonnet","gpt-4"] |
| mcp | {"server":"data-mcp","tools":["postgres_sync","mysql_replicate","mongodb_sync","redis_cache"]} |
| capabilities | ["Real-time replication","Cross-database sync","Schema migration","Conflict resolution"] |
| input | ["Source database config","Target database config","Sync rules","Transformation mappings"] |
| output | ["Synced data","Replication logs","Conflict reports","Migration status"] |
| languages | ["en"] |
| related_skills | ["etl-pipeline","sheets-automation","airtable-automation"] |
Comprehensive skill for database synchronization, replication, and data integration.
DATABASE SYNC PATTERNS:
┌─────────────────────────────────────────────────────────┐
│ ONE-WAY REPLICATION │
│ ┌──────────┐ ┌──────────┐ │
│ │ Master │ ──────▶ │ Replica │ │
│ └──────────┘ └──────────┘ │
└─────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────┐
│ BI-DIRECTIONAL SYNC │
│ ┌──────────┐ ┌──────────┐ │
│ │ Database │ ◀─────▶ │ Database │ │
│ │ A │ │ B │ │
│ └──────────┘ └──────────┘ │
└─────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────┐
│ HUB-AND-SPOKE │
│ ┌──────────┐ │
│ │ Spoke 1 │ │
│ └────┬─────┘ │
│ │ │
│ ┌──────────┐──┴──┌──────────┐ │
│ │ Spoke 2 │◀───▶│ Hub │◀────┬──────────┐ │
│ └──────────┘ └──────────┘ │ Spoke 3 │ │
│ └──────────┘ │
└─────────────────────────────────────────────────────────┘
sync_methods:
full_sync:
description: "Complete data refresh"
use_when:
- Initial sync
- Schema changes
- Disaster recovery
considerations:
- Downtime required
- Resource intensive
incremental_sync:
description: "Changes only"
sync_config:
source:
type: postgresql
host: "source-db.example.com"
port: 5432
database: "production"
credentials:
type: secret_manager
path: "db/source/credentials"
ssl: required
target:
type: mysql
host: "target-db.example.com"
port: 3306
database: "analytics"
credentials:
type: secret_manager
path: "db/target/credentials"
ssl: required
sync_settings:
mode: incremental
batch_size: 10000
parallel_tables: 4
retry_attempts: 3
checkpoint_interval: 5_minutes
table_mappings:
- source_table: users
target_table: dim_users
columns:
id: user_id
email: email_address
created_at: registration_date
status: user_status
transformations:
- column: status
transform: "UPPER(status)"
- column: email_address
transform: "LOWER(email)"
filters:
- "status != 'deleted'"
- "created_at > '2023-01-01'"
- source_table: orders
target_table: fact_orders
columns:
"*": "*" # All columns
exclude_columns:
- internal_notes
- deleted_at
incremental_key: updated_at
cdc_config:
method: logical_replication # or: trigger, polling
postgresql:
publication: "sync_publication"
slot: "sync_slot"
tables:
- users
- orders
- products
change_tracking:
capture_deletes: true
capture_before_values: true
output_format:
type: json
include:
- operation
- timestamp
- table
- key
- before
- after
cdc_events:
example_insert:
operation: INSERT
timestamp: "2024-01-15T10:30:00Z"
table: users
key: { id: 12345 }
after:
id: 12345
email: "user@example.com"
status: "active"
example_update:
operation: UPDATE
timestamp: "2024-01-15T10:31:00Z"
table: users
key: { id: 12345 }
before:
status: "active"
after:
status: "premium"
example_delete:
operation: DELETE
timestamp: "2024-01-15T10:32:00Z"
table: users
key: { id: 12345 }
before:
id: 12345
email: "user@example.com"
conflict_resolution:
strategies:
- name: last_write_wins
description: "Most recent update wins"
resolution: |
IF source.updated_at > target.updated_at
THEN use source
ELSE keep target
- name: source_priority
description: "Source always wins"
resolution: "always use source"
- name: merge
description: "Merge non-conflicting fields"
resolution: |
FOR each field:
IF only_one_changed: use_changed
IF both_changed: use source.field
- name: custom_rules
description: "Field-specific rules"
rules:
- field: quantity
strategy: sum
- field: status
strategy: priority_order
order: ["active", "pending", "inactive"]
- field: last_login
strategy: max
conflict_log:
format:
timestamp: "{{time}}"
table: "{{table}}"
key: "{{primary_key}}"
field: "{{conflicting_field}}"
source_value: "{{source.value}}"
target_value: "{{target.value}}"
resolution: "{{applied_strategy}}"
result: "{{final_value}}"
storage:
type: table
name: sync_conflicts
retention_days: 90
alerting:
threshold: 100 # conflicts per hour
notify: ["slack:#data-alerts"]
schema_sync:
mode: evolve # or: strict, ignore
operations:
add_column:
action: apply
default_value: null
remove_column:
action: warn
keep_data: true
modify_type:
action: review
safe_changes:
- varchar_expand
- int_to_bigint
rename_column:
action: manual
create_mapping: true
-- Example Migration: Add new column
ALTER TABLE users
ADD COLUMN IF NOT EXISTS
loyalty_tier VARCHAR(20) DEFAULT 'bronze';
-- Example Migration: Create sync tracking table
CREATE TABLE IF NOT EXISTS _sync_metadata (
table_name VARCHAR(100) PRIMARY KEY,
last_sync_at TIMESTAMP,
last_sync_key VARCHAR(255),
records_synced BIGINT,
status VARCHAR(20)
);
-- Example Migration: Add sync trigger
CREATE OR REPLACE FUNCTION track_changes()
RETURNS TRIGGER AS $$
BEGIN
INSERT INTO _change_log (
table_name, operation, key, changed_at
) VALUES (
TG_TABLE_NAME, TG_OP, NEW.id, NOW()
);
RETURN NEW;
END;
$$ LANGUAGE plpgsql;
DATABASE SYNC STATUS
═══════════════════════════════════════
OVERALL STATUS: ✓ Healthy
SOURCE: PostgreSQL (production)
TARGET: MySQL (analytics)
MODE: Incremental CDC
TABLES:
┌──────────────┬──────────┬───────────┬──────────┐
│ Table │ Status │ Lag │ Records │
├──────────────┼──────────┼───────────┼──────────┤
│ users │ ✓ Synced │ 2s │ 1.2M │
│ orders │ ✓ Synced │ 5s │ 8.5M │
│ products │ ✓ Synced │ 1s │ 50K │
│ events │ ⚠ Behind │ 2m 30s │ 45M │
└──────────────┴──────────┴───────────┴──────────┘
THROUGHPUT:
Current: 5,230 records/sec
Average: 4,850 records/sec
Peak: 12,400 records/sec
LAST 24 HOURS:
Records Synced: 45.2M
Errors: 23
Conflicts: 156
metrics:
- name: sync_lag_seconds
type: gauge
labels: [table_name, sync_job]
alert:
warning: "> 60"
critical: "> 300"
- name: records_synced_total
type: counter
labels: [table_name, operation]
- name: sync_errors_total
type: counter
labels: [table_name, error_type]
- name: conflict_count
type: counter
labels: [table_name, resolution_strategy]
pg_to_bigquery:
source:
type: postgresql
connection: "${PG_CONNECTION_STRING}"
tables:
- name: orders
incremental_key: updated_at
target:
type: bigquery
project: "my-project"
dataset: "analytics"
schedule: "*/5 * * * *" # Every 5 minutes
transform:
- type: add_metadata
columns:
_synced_at: "CURRENT_TIMESTAMP()"
_source: "'production'"
mysql_to_elasticsearch:
source:
type: mysql
tables:
- products
target:
type: elasticsearch
index: products_search
mapping:
id: _id
name:
type: text
analyzer: standard
description:
type: text
analyzer: english
category:
type: keyword
price:
type: float