mdcms/neuraldb-docs/pages/nql-hybrid.md

---
title: Hybrid Queries
sort: 120
section-id: query-language
keywords: hybrid queries, vector, relational, filters, combined, semantic search, metadata
description: Combining vector similarity and relational filters in NQL hybrid queries
language: en
---

# Hybrid Queries

Hybrid queries combine vector similarity search with relational filter predicates in a single SQL statement.

## Basic Hybrid Query

```sql
SELECT id, name, price, 1 - (embedding <=> $1) AS similarity
FROM products
WHERE category = 'electronics'
  AND stock > 0
  AND price < 500
ORDER BY embedding <=> $1
LIMIT 10;
```

## Query Planner Hints

```sql
-- Force pre-filter
SELECT /*+ PREFILTER */ id, name, 1 - (embedding <=> $1) AS score
FROM products WHERE category = 'electronics'
ORDER BY score DESC LIMIT 10;

-- Force post-filter
SELECT /*+ POSTFILTER */ id, name, 1 - (embedding <=> $1) AS score
FROM products WHERE price < 500
ORDER BY embedding <=> $1 LIMIT 10;
```

## Hybrid Full-Text + Vector (BM25)

```sql
WITH vector_search AS (
  SELECT id, ROW_NUMBER() OVER (ORDER BY embedding <=> $1) AS rank
  FROM documents ORDER BY embedding <=> $1 LIMIT 100
),
fts_search AS (
  SELECT id, ROW_NUMBER() OVER (ORDER BY ts_rank_cd(tsv, query) DESC) AS rank
  FROM documents, to_tsquery('english', $2) query
  WHERE tsv @@ query ORDER BY ts_rank_cd(tsv, query) DESC LIMIT 100
),
rrf AS (
  SELECT COALESCE(v.id, f.id) AS id,
    (COALESCE(1.0/(60+v.rank),0) + COALESCE(1.0/(60+f.rank),0)) AS rrf_score
  FROM vector_search v FULL OUTER JOIN fts_search f ON v.id = f.id
)
SELECT d.id, d.content, rrf.rrf_score
FROM rrf JOIN documents d ON d.id = rrf.id
ORDER BY rrf_score DESC LIMIT 10;
```

## Composite Scoring

```sql
SELECT id, name, price, rating,
  (0.7 * (1 - (embedding <=> $1))
   + 0.2 * (rating / 5.0)
   + 0.1 * (1 - EXTRACT(DAYS FROM NOW() - created_at) / 365.0)
  ) AS composite_score
FROM products
WHERE available = true AND price < $2
ORDER BY composite_score DESC LIMIT 20;
```