> ## Documentation Index
> Fetch the complete documentation index at: https://docs.dbdock.xyz/llms.txt
> Use this file to discover all available pages before exploring further.

# dbdock analyze

> Scan a database and print its shape, types, and inconsistencies.

```bash theme={null}
npx dbdock analyze <database-url>
```

`analyze` reads the structure of a database — MongoDB or PostgreSQL — and reports what's inside. Use it before running a cross-database migration to understand what you're migrating.

## Examples

### Analyze MongoDB

```bash theme={null}
npx dbdock analyze "mongodb://localhost:27017/myapp"
```

### Analyze PostgreSQL

```bash theme={null}
npx dbdock analyze "postgresql://user:pass@localhost:5432/myapp"
```

## What it reports

### For MongoDB

* Collection names and document counts
* Field names per collection
* Inferred types per field (with frequency if heterogeneous)
* Nesting depth
* Potential reference fields (`_id` patterns that look like foreign keys)
* Index coverage

### For PostgreSQL

* Table names and row counts
* Column types and nullability
* Primary and foreign keys
* Indexes
* Sequence/identity columns

### Sample output (MongoDB)

```
Database: myapp (mongodb://localhost:27017)
Collections: 4

┌──────────────┬──────────┬────────┬─────────┐
│ Collection   │ Documents│ Fields │ Indexes │
├──────────────┼──────────┼────────┼─────────┤
│ users        │   12,450 │     8  │    3    │
│ orders       │   48,910 │    12  │    5    │
│ products     │      820 │    14  │    2    │
│ reviews      │    3,180 │     6  │    1    │
└──────────────┴──────────┴────────┴─────────┘

users:
  _id            ObjectId     (unique)
  email          String       (unique, 12,450 values)
  name           String
  age            Number       (99.2% Int, 0.8% Double)  ⚠️ mixed types
  created_at     Date
  metadata       Object       (nested, depth 2)
  deleted_at     Date|null
  tags           Array<String>

⚠️ Inconsistencies found:
  • users.age has mixed numeric types (Int and Double)
  • orders.total has 12 documents missing the field
  • products.price has 3 documents with type String instead of Number
```

## What to do with the output

<CardGroup cols={2}>
  <Card title="Spot inconsistencies early" icon="triangle-exclamation">
    Mixed types and missing fields cause migration errors. Fix them in the source first when you can.
  </Card>

  <Card title="Plan the schema" icon="diagram-project">
    Decide which nested objects to flatten vs keep as jsonb.
  </Card>

  <Card title="Pick batch size" icon="layer-group">
    Huge collections need smaller batches (see `--batch-size`).
  </Card>

  <Card title="Export to config" icon="file-export">
    Save the proposed mapping with `dbdock migrate --export-config`.
  </Card>
</CardGroup>

## Read-only

`analyze` only reads — it doesn't modify the source database. Safe to run against production.

## See also

<CardGroup cols={2}>
  <Card title="dbdock migrate" icon="arrows-left-right" href="/migration/migrate">
    Run the actual migration.
  </Card>

  <Card title="Schema mapping" icon="diagram-project" href="/migration/schema-mapping">
    How DBDock maps types.
  </Card>
</CardGroup>