Hanzo DocDB

Hanzo DocDB is a managed document database that speaks the MongoDB wire protocol. Existing MongoDB drivers connect without changes, while your data is stored durably in PostgreSQL under the hood.

Provision a Database

Each database is a logical resource scoped to your organization and created through the control plane.

curl -X POST https://api.hanzo.ai/v1/docdb \
  -H "Authorization: Bearer hk-..." \
  -H "X-Org-Id: org_a1b2c3" \
  -H "Content-Type: application/json" \
  -d '{ "name": "app" }'

The response returns a MongoDB connection string (mongodb://...).

Connect

Any MongoDB driver works — DocDB implements the MongoDB 5.0+ wire protocol on port 27017.

from pymongo import MongoClient

client = MongoClient("mongodb://user:password@docdb.hanzo.ai:27017/app?tls=true")
db = client.app

db.orders.insert_one({ "id": "ord_123", "total": 99.0, "items": ["sku_1"] })

# Aggregation pipeline
pipeline = [
    { "$match": { "total": { "$gt": 50 } } },
    { "$group": { "_id": None, "revenue": { "$sum": "$total" } } },
]
print(list(db.orders.aggregate(pipeline)))

mongosh and the official Node.js, Go, Java, and Rust drivers all connect the same way.

Features

• MongoDB-compatible CRUD, query operators, and aggregation pipelines
• Secondary, compound, and TTL indexes
• BSON documents with standard _id semantics
• Backed by PostgreSQL — durable storage, continuous backups, and point-in-time recovery
• OpenTelemetry metrics and traces out of the box

DocDB suits flexible, schema-light document data. For relational data and SQL, use SQL; for embeddings and similarity search, use Vector.

Related

• SQL — the managed PostgreSQL that backs DocDB storage
• Vector — embeddings and semantic search
• Search — full-text and hybrid indexes over documents
• API Keys — authenticate with hk- keys
• API Reference — every endpoint at api.hanzo.ai