MongoDB¶

MongoDB is a popular, open source NoSQL database known for its flexibility, scalability, and wide adoption in a variety of applications.

omniload supports MongoDB as both a source and destination.

URI format¶

MongoDB supports two connection string formats:

Standard format (local/self-hosted)¶

mongodb://user:password@host:port

URI parameters:

user: the user name to connect to the database
password: the password for the user
host: the host address of the database server
port: the port number the database server is listening on, default is 27017 for MongoDB

SRV format (MongoDB Atlas)¶

mongodb+srv://user:password@cluster.xxxxx.mongodb.net/?retryWrites=true&w=majority

URI parameters:

user: the user name to connect to the database
password: the password for the user
cluster.xxxxx.mongodb.net: the cluster hostname provided by MongoDB Atlas
Query parameters like retryWrites and w are optional but recommended for Atlas connections

[!CAUTION] Do not put the database name at the end of the URI for MongoDB, instead make it a part of --source-table or --dest-table option as database.collection format.

The same URI structure can be used both for sources and destinations. You can read more about MongoDB’s connection string format here.

Source table format¶

The --source-table option for MongoDB supports two formats:

Basic format¶

database.collection

This performs a simple collection scan, equivalent to db.collection.find().

Custom aggregation format¶

database.collection:[aggregation_pipeline]

This allows you to specify a custom MongoDB aggregation pipeline as a JSON array.

Custom aggregations¶

omniload supports custom MongoDB aggregation pipelines, similar to how SQL sources support custom queries. This allows you to perform complex data transformations, filtering, and projections directly in MongoDB before the data is ingested.

Basic syntax¶

Use the following format for custom aggregations:

omniload ingest \
  --source-uri "mongodb://user:password@host:port" \
  --source-table 'database.collection:[{"$match": {...}}, {"$project": {...}}]'

Examples¶

Simple filtering¶

omniload ingest \
  --source-uri "mongodb://localhost:27017" \
  --source-table 'mydb.users:[{"$match": {"status": "active"}}]'

Complex aggregation with grouping¶

omniload ingest \
  --source-uri "mongodb://localhost:27017" \
  --source-table 'mydb.orders:[
    {"$match": {"status": "completed"}},
    {"$group": {
      "_id": "$customer_id",
      "total_orders": {"$sum": 1},
      "total_amount": {"$sum": "$amount"}
    }}
  ]'

Projection and transformation¶

omniload ingest \
  --source-uri "mongodb://localhost:27017" \
  --source-table 'mydb.products:[
    {"$project": {
      "name": 1,
      "price": 1,
      "category": 1,
      "price_usd": {"$multiply": ["$price", 1.1]}
    }}
  ]'

Incremental loads with custom aggregations¶

Custom aggregations support incremental loading when combined with the --incremental-key option. The incremental key must be included in the projected fields of your aggregation pipeline.

Using interval placeholders¶

You can use :interval_start and :interval_end placeholders in your aggregation pipeline, which will be automatically replaced with the actual datetime values during incremental loads:

omniload ingest \
  --source-uri "mongodb://localhost:27017" \
  --source-table 'mydb.events:[
    {"$match": {
      "created_at": {
        "$gte": ":interval_start",
        "$lt": ":interval_end"
      }
    }},
    {"$project": {
      "_id": 1,
      "event_type": 1,
      "user_id": 1,
      "created_at": 1
    }}
  ]' \
  --incremental-key "created_at"

Requirements for incremental loads¶

When using incremental loads with custom aggregations:

Incremental key projection: The field specified in --incremental-key must be included in your projection
Datetime type: The incremental key should be a datetime field
Pipeline validation: omniload validates that your aggregation pipeline properly projects the incremental key

Validation and error handling¶

omniload performs several validations on custom aggregation pipelines:

JSON validation: Ensures the aggregation pipeline is valid JSON
Array format: Aggregation pipelines must be JSON arrays
Incremental key validation: When using --incremental-key, validates that the key is projected in the pipeline
Clear error messages: Provides specific error messages for common issues

Limitations¶

Parallel loading: Custom aggregations don’t support parallel loading due to MongoDB cursor limitations. The loader automatically falls back to sequential processing.
Arrow format: When using Arrow data format with custom aggregations, data is converted to Arrow format after loading rather than using native MongoDB Arrow integration.

Performance considerations¶

Use $match stages early in your pipeline to filter data as soon as possible
Add appropriate indexes to support your aggregation pipeline
Consider using $limit to restrict the number of documents processed
For large datasets, MongoDB’s allowDiskUse: true option is automatically enabled for aggregation pipelines

Using MongoDB Atlas as a source¶

MongoDB Atlas can be used as a source to extract data using the SRV connection string format.

omniload ingest \
  --source-uri "mongodb+srv://username:password@cluster0.xxxxx.mongodb.net/?retryWrites=true&w=majority" \
  --source-table "mydb.users" \
  --dest-uri "duckdb:///local.duckdb" \
  --dest-table "analytics.users"

[!NOTE] When using MongoDB Atlas as a source, ensure your IP address is whitelisted in Network Access settings. You can find this under Security > Network Access in your Atlas dashboard.

All the custom aggregation features described above work with MongoDB Atlas as well:

omniload ingest \
  --source-uri "mongodb+srv://username:password@cluster0.xxxxx.mongodb.net/?retryWrites=true&w=majority" \
  --source-table 'mydb.orders:[{"$match": {"status": "completed"}}]' \
  --dest-uri "duckdb:///local.duckdb" \
  --dest-table "analytics.completed_orders"

Using MongoDB as a destination¶

MongoDB can be used as a destination to load data from various sources. The --dest-table option follows the same format: database.collection.

MongoDB Atlas¶

omniload ingest \
  --source-uri "postgres://user:pass@localhost:5432/mydb" \
  --source-table "public.users" \
  --dest-uri "mongodb+srv://username:password@cluster0.xxxxx.mongodb.net/?retryWrites=true&w=majority" \
  --dest-table "mydb.users"

[!NOTE] When using MongoDB Atlas as a destination, ensure your IP address is whitelisted in Network Access settings.

Local MongoDB with authentication¶

omniload ingest \
  --source-uri "csv:///path/to/data.csv" \
  --source-table "data" \
  --dest-uri "mongodb://username:password@localhost:27017/?authSource=admin" \
  --dest-table "mydb.mycollection"

Local MongoDB without authentication¶

omniload ingest \
  --source-uri "csv:///path/to/data.csv" \
  --source-table "data" \
  --dest-uri "mongodb://localhost:27017" \
  --dest-table "mydb.mycollection"

[!TIP] By default, omniload uses a “replace” strategy which deletes existing data in the collection before loading new data. The target database and collection will be created automatically if they don’t exist.