---
title: Create Your First Index
description: Create a ParadeDB index over your table
canonical: https://www.paradedb.com/docs/start/create-your-first-index
---

Create a ParadeDB index over the `mock_items` table from [Configure Your
Environment](/start/configure-your-environment). The same index supports text
search, vector search, filtering, sorting, and aggregations in the next page.

<CodeGroup>
```sql SQL
CREATE INDEX search_idx ON mock_items
USING paradedb (
  id,
  description,
  embedding vector_cosine_ops,
  category,
  rating,
  in_stock,
  created_at,
  last_updated_date,
  latest_available_time,
  metadata,
  weight_range
)
WITH (key_field='id');
```

```ts Drizzle
import { sql } from "drizzle-orm";

await db.execute(sql`
  CREATE INDEX search_idx ON mock_items
  USING paradedb (
    id,
    description,
    embedding vector_cosine_ops,
    category,
    rating,
    in_stock,
    created_at,
    last_updated_date,
    latest_available_time,
    metadata,
    weight_range
  )
  WITH (key_field='id')
`);
```

```python Django
from django.db import connection

with connection.cursor() as cursor:
    cursor.execute("""
        CREATE INDEX search_idx ON mock_items
        USING paradedb (
          id,
          description,
          embedding vector_cosine_ops,
          category,
          rating,
          in_stock,
          created_at,
          last_updated_date,
          latest_available_time,
          metadata,
          weight_range
        )
        WITH (key_field='id')
    """)
```

```python SQLAlchemy
from sqlalchemy import text

with engine.begin() as conn:
    conn.execute(text("""
        CREATE INDEX search_idx ON mock_items
        USING paradedb (
          id,
          description,
          embedding vector_cosine_ops,
          category,
          rating,
          in_stock,
          created_at,
          last_updated_date,
          latest_available_time,
          metadata,
          weight_range
        )
        WITH (key_field='id')
    """))
```

```ruby Rails
ActiveRecord::Base.connection.execute <<~SQL
  CREATE INDEX search_idx ON mock_items
  USING paradedb (
    id,
    description,
    embedding vector_cosine_ops,
    category,
    rating,
    in_stock,
    created_at,
    last_updated_date,
    latest_available_time,
    metadata,
    weight_range
  )
  WITH (key_field='id');
SQL
```

```cs EF Core
await dbContext.Database.ExecuteSqlRawAsync("""
    CREATE INDEX search_idx ON mock_items
    USING paradedb (
      id,
      description,
      embedding vector_cosine_ops,
      category,
      rating,
      in_stock,
      created_at,
      last_updated_date,
      latest_available_time,
      metadata,
      weight_range
    )
    WITH (key_field='id');
    """);
```

</CodeGroup>

<Note>
  If `search_idx` already exists, drop it first with `DROP INDEX search_idx;`.
</Note>

The first indexed column, `id`, is also the `key_field`. ParadeDB uses the key
field as the row's stable identifier inside the index. In your own schema, use a
primary key or another column with a `UNIQUE` constraint. See [Choosing a Key
Field](/reference/indexing/create-index#choosing-a-key-field) for the full
rules.

Everything after `id` is a field you can search, filter, sort, group, or
aggregate. The `description` column is indexed for full-text search, `embedding`
is indexed for vector search, and fields like `rating`, `category`, and
`created_at` are available for filters, Top K queries, and facets.

For production schemas, define this index in your migration system instead of
running ad hoc SQL. The full [Create an
Index](/reference/indexing/create-index) reference includes framework-native
examples and tokenizer options.

Next, [run your first queries](/start/run-queries).