# From pgvector
# Migrate from pgvector to Qdrant

## What You Need from Postgres

- **Connection URL** — a standard Postgres connection string
- **Table name** — the table containing your vector data

## Concept Mapping

| pgvector | Qdrant | Notes |
| :--- | :--- | :--- |
| Table | Collection | One-to-one mapping |
| Row | Point | Each row becomes a point |
| `vector` column | Vector | Mapped automatically |
| Other columns | Payload | All non-vector columns become payload fields |
| `vector_cosine_ops` | `Cosine` | pgvector returns distance (1 - similarity); Qdrant returns similarity |
| `vector_l2_ops` | `Euclid` | Direct mapping |
| `vector_ip_ops` | `Dot` | pgvector uses negative inner product for ordering; scores will be inverted |

## Run the Migration

```bash
docker run --net=host --rm -it registry.cloud.qdrant.io/library/qdrant-migration pg \
    --pg.url 'postgres://user:password@host:5432/dbname' \
    --pg.table 'your_embeddings_table' \
    --pg.key-column 'id' \
    --qdrant.url 'https://your-instance.cloud.qdrant.io:6334' \
    --qdrant.api-key 'your-qdrant-api-key' \
    --qdrant.collection 'your-collection'
```

### Selecting Specific Columns

By default, all columns are migrated. Use `--pg.columns` to select specific ones:

```bash
docker run --net=host --rm -it registry.cloud.qdrant.io/library/qdrant-migration pg \
    --pg.url 'postgres://user:password@host:5432/dbname' \
    --pg.table 'your_embeddings_table' \
    --pg.key-column 'id' \
    --pg.columns 'id,embedding,title,category' \
    --qdrant.url 'https://your-instance.cloud.qdrant.io:6334' \
    --qdrant.api-key 'your-qdrant-api-key' \
    --qdrant.collection 'your-collection'
```

### All pgvector-Specific Flags

| Flag | Required | Description |
| :--- | :--- | :--- |
| `--pg.url` | Yes | Postgres connection string |
| `--pg.table` | Yes | Table name to migrate |
| `--pg.key-column` | Yes | Column to use as point ID |
| `--pg.columns` | No | Comma-separated columns to migrate (default: all) |
| `--migration.num-workers` | No | Parallel workers (default: number of CPU cores) |

### Qdrant-Side Options

| Flag | Default | Description |
| :--- | :--- | :--- |
| `--qdrant.distance-metric` | `cosine` | Distance metric per vector field (map format) |

## Gotchas

- **Partition structure:** If you had manual partitions in pgvector (common at scale), verify that all partitions were migrated, not just the primary table.
- **NULL handling:** PostgreSQL NULLs may be dropped during export. Check that optional fields are represented correctly in Qdrant payloads.
- **Index type and recall:** pgvector supports IVFFlat and HNSW. If your baseline was captured with IVFFlat (lower recall), Qdrant's HNSW may return better results. This looks like a "mismatch" but is an improvement.
- **Row count approximation:** Postgres's `n_live_tup` is an estimate, not an exact count. Use `SELECT COUNT(*) FROM your_table` for accurate comparison during [migration verification](/documentation/migration-guidance/index.md).

## After Migration: Keeping Postgres and Qdrant in Sync

If you continue using Postgres as your source of truth alongside Qdrant, you'll need a sync strategy. The [Data Synchronization Guide](/documentation/data-synchronization/index.md) covers three approaches from simple dual-writes to production-grade Change Data Capture.

## Next Steps

After migration, verify your data arrived correctly with the [Migration Verification Guide](/documentation/migration-guidance/index.md).