add how databend Copy-Free data sharing works (#2396)

Author: BohuTANG

docs/en/guides/81-how-databend-works/04-how-databend-share-data-works.md

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+---
+title: How Databend Copy-Free Data Sharing Works
+---
+
+## What is Data Sharing?
+
+Different teams need different parts of the same data. Traditional solutions copy data multiple times - expensive and hard to maintain.
+
+Databend's **[ATTACH TABLE](/sql/sql-commands/ddl/table/attach-table)** solves this elegantly: create multiple "views" of the same data without copying it. This leverages Databend's **true compute-storage separation** - whether using cloud storage or on-premise object storage: **store once, access everywhere**.
+
+Think of ATTACH TABLE like computer shortcuts - they point to the original file without duplicating it.
+
+```
+                Object Storage (S3, MinIO, Azure, etc.)
+                         ┌─────────────┐
+                         │ Your Data   │
+                         └──────┬──────┘
+                                │
+        ┌───────────────────────┼───────────────────────┐
+        │                       │                       │
+        ▼                       ▼                       ▼
+┌─────────────┐         ┌─────────────┐         ┌─────────────┐
+│ Marketing   │         │  Finance    │         │   Sales     │
+│ Team View   │         │ Team View   │         │ Team View   │
+└─────────────┘         └─────────────┘         └─────────────┘
+```
+
+## How to Use ATTACH TABLE
+
+**Step 1: Find your data location**
+```sql
+SELECT snapshot_location FROM FUSE_SNAPSHOT('default', 'company_sales');
+-- Result: 1/23351/_ss/... → Data at s3://your-bucket/1/23351/
+```
+
+**Step 2: Create team-specific views**
+```sql
+-- Marketing: Customer behavior analysis
+ATTACH TABLE marketing_view (customer_id, product, amount, order_date) 
+'s3://your-bucket/1/23351/' CONNECTION = (AWS_KEY_ID = 'xxx', AWS_SECRET_KEY = 'yyy');
+
+-- Finance: Revenue tracking
+ATTACH TABLE finance_view (order_id, amount, profit, order_date) 
+'s3://your-bucket/1/23351/' CONNECTION = (AWS_KEY_ID = 'xxx', AWS_SECRET_KEY = 'yyy');
+
+-- HR: Employee info without salaries
+ATTACH TABLE hr_employees (employee_id, name, department) 
+'s3://data/1/23351/' CONNECTION = (...);
+
+-- Development: Production structure without sensitive data
+ATTACH TABLE dev_customers (customer_id, country, created_date) 
+'s3://data/1/23351/' CONNECTION = (...);
+```
+
+**Step 3: Query independently**
+```sql
+-- Marketing analyzes trends
+SELECT product, COUNT(*) FROM marketing_view GROUP BY product;
+
+-- Finance tracks profit
+SELECT order_date, SUM(profit) FROM finance_view GROUP BY order_date;
+```
+
+## Key Benefits
+
+**Real-Time Updates**: When source data changes, all attached tables see it instantly
+```sql
+INSERT INTO company_sales VALUES (1001, 501, 'Laptop', 1299.99, 299.99, 'user@email.com', '2024-01-20');
+SELECT COUNT(*) FROM marketing_view WHERE order_date = '2024-01-20'; -- Returns: 1
+```
+
+**Column-Level Security**: Teams only see what they need - Marketing can't see profit, Finance can't see customer emails
+
+**Strong Consistency**: Never read partial updates, always see complete snapshots - perfect for financial reporting and compliance
+
+**Full Performance**: All indexes work automatically, same speed as regular tables
+
+## Why This Matters
+
+| Traditional Approach | Databend ATTACH TABLE |
+|---------------------|----------------------|
+| Multiple data copies | Single copy shared by all |
+| ETL delays, sync issues | Real-time, always current |
+| Complex maintenance | Zero maintenance |
+| More copies = more security risk | Fine-grained column access |
+| Slower due to data movement | Full optimization on original data |
+
+## How It Works Under the Hood
+
+```
+Query: SELECT product, SUM(amount) FROM marketing_view GROUP BY product
+
+┌─────────────────────────────────────────────────────────────────┐
+│                    Query Execution Flow                         │
+└─────────────────────────────────────────────────────────────────┘
+
+    User Query
+        │
+        ▼
+┌───────────────────┐    ┌─────────────────────────────────────┐
+│ 1. Read Snapshot  │───►│ s3://bucket/1/23351/_ss/            │
+│    Metadata       │    │ Get current table state             │
+└───────────────────┘    └─────────────────────────────────────┘
+        │
+        ▼
+┌───────────────────┐    ┌─────────────────────────────────────┐
+│ 2. Apply Column   │───►│ Filter: customer_id, product,       │
+│    Filter         │    │         amount, order_date          │
+└───────────────────┘    └─────────────────────────────────────┘
+        │
+        ▼
+┌───────────────────┐    ┌─────────────────────────────────────┐
+│ 3. Check Stats &  │───►│ • Segment min/max values            │
+│    Indexes        │    │ • Bloom filters                     │
+└───────────────────┘    │ • Aggregate indexes                 │
+        │                └─────────────────────────────────────┘
+        ▼
+┌───────────────────┐    ┌─────────────────────────────────────┐
+│ 4. Smart Data     │───►│ Skip irrelevant blocks              │
+│    Fetching       │    │ Download only needed data from _b/  │
+└───────────────────┘    └─────────────────────────────────────┘
+        │
+        ▼
+┌───────────────────┐    ┌─────────────────────────────────────┐
+│ 5. Local          │───►│ Full optimization & parallelism     │
+│    Execution      │    │ Process with all available indexes  │
+└───────────────────┘    └─────────────────────────────────────┘
+        │
+        ▼
+    Results: Product sales summary
+```
+
+Multiple Databend clusters can execute this flow simultaneously without coordination - true compute-storage separation in action.
+
+ATTACH TABLE represents a fundamental shift: **from copying data for each use case to one copy with many views**. Whether in cloud or on-premise environments, Databend's architecture enables powerful, efficient data sharing while maintaining enterprise-grade consistency and security.