MongoDB

SoftDB supports MongoDB with multi-database browsing, collection exploration, schema inference from sampled documents, a native JSON Schema Validation editor, and a JSON-based query interface.

Quick Setup

1. Open the Connection Hub and click New Connection.

2. Select MongoDB as the database type.

3. For a local server, fill in:

   • Host: localhost
   • Port: 27017
   • Database: optional — leave blank to browse all databases

4. For MongoDB Atlas or any mongodb+srv:// connection, toggle Use URI and paste your full connection string.

5. Click Test Connection, then Save.

Connection Settings

Field	Default	Notes
Host	localhost	MongoDB server hostname or IP
Port	27017	Standard MongoDB port
Username	—	Optional for local servers without auth
Password	—	Stored encrypted
Database	—	Optional. Leave blank to browse all databases
URI	—	Full connection string (URI mode only)

URI Mode for Atlas

Toggle Use URI to enter a full MongoDB connection string. This is the recommended approach for MongoDB Atlas:

mongodb+srv://username:password@cluster0.abc123.mongodb.net/mydb?retryWrites=true&w=majority

When using URI mode, the host, port, username, password, and database fields are ignored. SoftDB parses the database name from the URI path if present.

Multi-Database Browsing

When you leave the Database field blank, SoftDB calls listDatabaseNames and filters out system databases (admin, local, config). The sidebar shows a three-level tree:

Connection
└── my_app
    ├── users
    ├── orders
    └── products
└── analytics
    └── events

Clicking a collection opens it in the table explorer. SoftDB samples up to 100 documents to infer the collection’s field names and BSON types.

JSON Command Syntax

Caution

SoftDB uses a JSON command format for MongoDB queries, not the JavaScript shell syntax (db.collection.find()). Every query is a JSON object with a collection field and an action field.

The basic structure is:

{
  "collection": "users",
  "action": "find",
  "filter": {},
  "limit": 100
}

If you omit action, it defaults to find.

Supported actions

Action	Description
find	Query documents with optional filter, limit, and skip
count	Count documents matching a filter
insert	Insert a single document
delete	Delete documents matching a filter
updateOne	Update the first matching document
updateMany	Update all matching documents
aggregate	Run an aggregation pipeline
distinct	Get distinct values for a field
createIndex	Create an index on a collection
dropIndex	Drop a named index
explain	Get the query execution plan

Query Examples

Find with filter

{
  "collection": "users",
  "action": "find",
  "filter": { "age": { "$gt": 25 } },
  "limit": 10
}

Count documents

{
  "collection": "orders",
  "action": "count",
  "filter": { "status": "pending" }
}

Aggregation pipeline

{
  "collection": "orders",
  "action": "aggregate",
  "pipeline": [
    { "$match": { "status": "completed" } },
    { "$group": { "_id": "$customer_id", "total": { "$sum": "$amount" } } },
    { "$sort": { "total": -1 } },
    { "$limit": 10 }
  ]
}

Update documents

{
  "collection": "users",
  "action": "updateMany",
  "filter": { "plan": "free" },
  "update": { "$set": { "trial_expires": null } }
}

Insert a document

{
  "collection": "products",
  "action": "insert",
  "document": {
    "name": "Widget Pro",
    "price": 29.99,
    "tags": ["hardware", "featured"]
  }
}

Distinct values

{
  "collection": "orders",
  "action": "distinct",
  "field": "status"
}

Batch queries

You can run multiple queries in one execution by wrapping them in a JSON array. Results are merged into a single result set with a __collection__ column added:

[
  { "collection": "users", "action": "count" },
  { "collection": "orders", "action": "count" }
]

Schema Inference

SoftDB doesn’t require a fixed schema for MongoDB collections. When you open a collection, it samples up to 100 documents and infers field names and BSON types. The inferred schema appears in the sidebar column list and is used for AI autocomplete suggestions.

BSON types are mapped to readable names: string, int, long, double, bool, object, array, objectId, date, timestamp, decimal, binData, regex, and null.

JSON Schema Validation Editor

Each collection can have a JSON Schema validator that MongoDB enforces on insert and update. SoftDB includes a dedicated editor for this:

1. Open a collection in the table explorer.
2. Click the Schema tab (or the schema icon in the toolbar).
3. Edit the JSON Schema in the Monaco editor.
4. Click Apply to save the validator to MongoDB.

SoftDB applies validators with validationLevel: "moderate" and validationAction: "warn" by default, so existing documents that don’t match the schema won’t cause errors — only new writes are checked.

Troubleshooting

Connection refused

failed to ping mongodb: server selection error: ... connection refused

MongoDB isn’t running, or it’s listening on a different port. Check with systemctl status mongod or brew services list. Verify the port in /etc/mongod.conf.

Authentication failed

failed to ping mongodb: (AuthenticationFailed) Authentication failed

Wrong username or password, or the user doesn’t exist in the admin database. Check your credentials and ensure the user has the right roles.

Atlas connection string format

Atlas connection strings use mongodb+srv:// and require the Use URI toggle. The standard host:port fields don’t work for Atlas. Copy the connection string from the Atlas dashboard (Connect > Drivers) and paste it into the URI field.

Make sure your IP address is in the Atlas IP Access List, and that the database user has the correct permissions.