tap-mongodb

tap-mongodb is a Singer tap for extracting data from a MongoDB or AWS DocumentDB database.

Built with the Meltano Tap SDK for Singer Taps.

Replication Modes

The tap supports two replication modes:

1. INCREMENTAL (Default)

• Extracts records directly from collections
• Uses _id field as replication key
• Suitable for regular MongoDB instances
• No special infrastructure required

2. LOG_BASED (CDC - Change Data Capture)

• Captures change events via MongoDB Change Streams
• Tracks insert, update, replace, and delete operations
• Requires MongoDB replica set or sharded cluster
• Includes operation metadata, cluster timestamps, and full document state
• Automatically exits after 10 seconds of inactivity (production-ready)

Arrow BATCH mode

Setting batch_config with the arrow format makes INCREMENTAL streams write Apache Arrow IPC files and emit Singer BATCH messages instead of one RECORD message per document. Documents are decoded from raw BSON with PyMongoArrow, so most values never become Python objects.

{
  "batch_config": {
    "encoding": {"format": "arrow"},
    "storage": {"root": "file:///tmp/batches"},
    "batch_size": 100000
  }
}

batch_size defaults to 100,000 rows per file, and storage.root to a singer-sdk folder in the OS temp directory. A STATE message follows each file, so an interrupted sync resumes after the last file written. LOG_BASED streams keep emitting RECORD messages.

Records have the same fields as in RECORD mode, with document as an Arrow struct. Before extracting, the tap scans the BSON types of each top-level document field, and converts each field as follows:

Top-level field	In the document struct
One of double, string, bool, int/long, date, ObjectId	The matching Arrow type: double, string, bool, int64, UTC timestamp, hex string
Another scalar type (decimal, binary, ...)	The string RECORD mode emits, e.g. "1.5"
Sub-documents and arrays	JSON
Values of more than one BSON type	JSON, with a warning naming the field

JSON values use Arrow's canonical arrow.json extension type. Targets built with the Meltano Singer SDK (0.55.0b7 or later) decode them, so they receive the same documents as in RECORD mode. Other readers that understand the type, such as DuckDB, get JSON values, and the rest get the JSON text.

The document struct has a fixed set of fields, so a field missing from a document and a field set to null both come through as null (SQL semantics). In RECORD mode, a missing field is left out of the document object instead.

A sync extracts the documents that existed when it started; documents inserted during the sync are picked up by the next one. If a document is updated during the sync so that a field no longer matches its scanned type, the sync fails with an error asking to run it again.

Flat document layout

By default, each record carries the whole document in a single document object. With document_layout: flat, each document field you declare becomes its own typed column instead, in RECORD and BATCH mode alike. Declare the fields as properties of the stream's schema, for example with Meltano's schema extra:

plugins:
  extractors:
  - name: tap-mongodb
    config:
      document_layout: flat
    schema:
      users:
        name: {type: [string, "null"]}
        age: {type: [integer, "null"]}
        joined_at: {type: [string, "null"], format: date-time}
        manager_id: {type: [string, "null"]}
        address: {type: [object, "null"]}

Property names are the documents' top-level field names. The record envelope (replication_key, object_id, namespace, ...) stays, and the document property is left out.

Declared type	Accepted BSON values	Column
integer	int, long	integer
number	int, long, double	number (NaN and infinities become null)
boolean	bool	boolean
string with format: date-time	date	timestamp
string	string, and types JSON has no equivalent for (ObjectId, Decimal128, binary, ...)	string: an ObjectId becomes its hex string, a Decimal128 like "1.5"
object, array	sub-document, array	JSON
any other declaration, e.g. [integer, string]	any	JSON

• Type mismatches fail the sync, naming the field and a document: e.g. a double in an integer field. With Arrow batches, the tap checks the declared fields' types in the sync's range before writing any file, so nothing is written for a failing sync.
• Undeclared fields are dropped, with a warning naming them.
• Missing fields are null, like explicit null values.
• Deselected fields aren't extracted or checked.
• Field names containing . or starting with $ aren't supported yet.

Installation

Install from GitHub:

pipx install git+https://github.com/MeltanoLabs/tap-mongodb.git@main

# or

uv tool install git+https://github.com/MeltanoLabs/tap-mongodb.git@main

Configuration

Accepted Config Options

Setting	Type	Required	Default	Description
database	string	True	-	Database from which records will be extracted.
mongodb_connection_string	password	False	-	MongoDB connection string. See the MongoDB documentation for specification. The username and password included in this string must be url-encoded - the tap will not url-encode it.
documentdb_credential_json_string	password	False	-	JSON string with keys 'username', 'password', 'engine', 'host', 'port', 'dbClusterIdentifier' or 'dbName', 'ssl'. See example and strucure in the AWS documentation here. The password from this JSON object will be url-encoded by the tap before opening the database connection. The intent of this setting is to enable management of an AWS DocumentDB database credential via AWS SecretsManager
documentdb_credential_json_extra_options	string	False	-	JSON string containing key-value pairs which will be added to the connection string options when using documentdb_credential_json_string. For example, when set to the string {"tls":"true","tlsCAFile":"my-ca-bundle.pem"}, the options tls=true&tlsCAFile=my-ca-bundle.pem will be passed to the MongoClient.
datetime_conversion	string	False	datetime	Parameter passed to MongoClient 'datetime_conversion' parameter. See documentation at https://pymongo.readthedocs.io/en/stable/examples/datetimes.html#handling-out-of-range-datetimes for details. The default value is 'datetime', which will throw a bson.errors.InvalidBson error if a document contains a date outside the range of datetime.MINYEAR (year 1) to datetime.MAXYEAR (9999).
prefix	string	False	''	An optional prefix which will be added to the name of each stream.
filter_collections	string[]	False	[]	Collections to discover (default: all) - filtering is case-insensitive. Useful for improving catalog discovery performance.
start_date	date_iso8601	False	1970-01-01	Start date - used for incremental replication only. In log-based replication mode, this setting is ignored.
add_record_metadata	boolean	False	False	When true, _sdc metadata fields will be added to records produced by the tap.
allow_modify_change_streams	boolean	False	False	In AWS DocumentDB (unlike MongoDB), change streams must be enabled specifically (see the documentation here ). If attempting to open a change stream against a collection on which change streams have not been enabled, an OperationFailure error will be raised. If this property is set to True, when this error is seen, the tap will execute an admin command to enable change streams and then retry the read operation. Note: this may incur new costs in AWS DocumentDB.
operation_types	list(string)	False	create,delete,insert,replace,update	List of MongoDB change stream operation types to include in tap output. The default behavior is to limit to document-level operation types. See full list of operation types in the MongoDB documentation. Note that the list of allowed_values for this property includes some values not available to all MongoDB versions.
change_stream_pipeline	list(object)	False	[]	Optional list of MongoDB aggregation pipeline stages appended to the change stream (passed as the pipeline argument to collection.watch()). Only used in LOG_BASED replication mode. Can be used to reduce event size server-side to avoid MongoDB's 16MB BSON limit - e.g. [{"$unset": "updateDescription"}] drops a field the tap never reads - or for server-side filtering via $match, complementing operation_types. No validation is performed; a pipeline that removes _id, operationType, clusterTime, ns, or both fullDocument/documentKey will cause tap errors.
batch_config	object	False	-	Opts into Singer BATCH messages. With encoding.format: arrow, incremental streams write Apache Arrow IPC files decoded straight from BSON. See Arrow BATCH mode.
document_layout	string	False	object	object emits each document as a single document object. flat emits each document field declared in the stream's schema as its own column. See Flat document layout.

Configure using environment variables

This Singer tap will automatically import any environment variables within the working directory's .env if the --config=ENV is provided, such that config values will be considered if a matching environment variable is set either in the terminal context or in the .env file.

Source Configuration

MongoDB

AWS DocumentDB

Source Authentication and Authorization

Incremental replication mode

In order to run tap-mongodb in incremental replication mode, the credential used must have read privileges to the collections from which you wish to extract records. If your credential has the readAnyDatabase@admin permission, for example, or read@test_database (where test_database is the database setting in the tap's configuration), that should be sufficient.

Collection-level read permissions are untested but are expected to work as well:

privileges: [
    {resource: {db: "test_database", collection: "TestOrders"}, actions: ["find"]}
]

The above collection-level read permission should allow the tap to extract from the test_database.TestOrders collection in incremental replication mode.

Log-based replication

In order to run tap-mongodb in log-based replication mode, which extracts records via the database's Change Streams API, MongoDB and AWS DocumentDB have different requirements around permissions.

In MongoDB, the credential must have both find and changeStreams permissions on a database collection in order to use tap-mongodb in log-based replication mode. The readAnyDatabase@admin built-in role provides this for all databases, while read@test_database will provide the necessary access for all collections in the test_database database.

Usage

You can easily run tap-mongodb by itself or in a pipeline using Meltano.

Executing the Tap Directly

tap-mongodb --version
tap-mongodb --help
tap-mongodb --config CONFIG --discover > ./catalog.json

Change Data Capture (LOG_BASED Mode)

The tap supports real-time change data capture using MongoDB Change Streams. This mode captures insert, update, replace, and delete operations as they occur.

Requirements

• MongoDB: Replica set (3+ nodes) or sharded cluster
• AWS DocumentDB: Cluster mode with change streams enabled
• Permissions: find and changeStream permissions on collections

Quick Start with Meltano

This repository includes a complete Docker-based testing setup with a 3-node MongoDB replica set.

1. Start MongoDB Replica Set

# Start 3-node replica set
docker compose up -d

# Wait for initialization (30-45 seconds)
docker compose ps
docker exec mongodb-primary mongosh --eval "rs.status()" --quiet

2. Configure CDC Plugin

The meltano.yml includes a pre-configured CDC plugin that inherits from the base tap:

- name: tap-mongodb-cdc
  inherit_from: tap-mongodb
  config:
    database: test
    mongodb_connection_string: mongodb://localhost:27017/?replicaSet=rs0&directConnection=true
  metadata:
    '*':
      replication-method: LOG_BASED
      replication-key: replication_key

3. Run CDC Sync

# Install the CDC plugin (first time only)
meltano install extractor tap-mongodb-cdc

# Run CDC sync
meltano run tap-mongodb-cdc target-jsonl

The tap will:

1. Open a change stream for each collection
2. Yield a resume token to track position
3. Process any existing change events
4. Automatically exit after 10 seconds of inactivity

CDC Output Format

Each CDC record includes:

{
  "operation_type": "insert",
  "cluster_time": "2025-11-19T20:28:33+00:00",
  "namespace": {
    "database": "test",
    "collection": "users"
  },
  "document": {
    "_id": "...",
    "name": "John Doe",
    "email": "john@example.com"
  },
  "replication_key": "82691E3EFE000000012B0429296E1404"
}

Operation Types:

• insert - New documents created (includes full document)
• update - Documents modified (includes full document via updateLookup)
• replace - Documents replaced entirely (includes full document)
• delete - Documents removed (includes only _id)

Testing CDC Locally

Seed Test Data

# Generate initial test data (users and posts)
uv run docker/seed-cdc-test-data.py

# Run initial sync to establish change stream position
meltano run --full-refresh tap-mongodb-cdc target-jsonl

# Simulate CDC events (inserts, updates, deletes, replaces)
uv run docker/seed-cdc-test-data.py --simulate-changes

# Capture the changes
meltano run tap-mongodb-cdc target-jsonl

# View captured events by operation type
grep '"operation_type"' output/*.jsonl | \
  sed 's/.*"operation_type": "\([^"]*\)".*/\1/' | sort | uniq -c

Full End-to-End Test

# Complete test workflow
docker compose up -d && sleep 30
uv run docker/seed-cdc-test-data.py
meltano run tap-mongodb-cdc target-jsonl
uv run docker/seed-cdc-test-data.py --simulate-changes
meltano run tap-mongodb-cdc target-jsonl

Resume Tokens and State

MongoDB change streams use resume tokens to track position in the oplog. The tap:

• Stores resume tokens in state after each sync
• Can resume from the exact position after crashes or restarts
• Handles oplog window expiration gracefully (MongoDB 4.2+)

Connection String Format

MongoDB:

mongodb://localhost:27017/?replicaSet=rs0&directConnection=true

DocumentDB:

mongodb://username:password@cluster.region.docdb.amazonaws.com:27017/?replicaSet=rs0&tls=true&tlsCAFile=rds-combined-ca-bundle.pem

Key parameters:

• replicaSet=rs0 - Required for change streams
• directConnection=true - Recommended when connecting from outside Docker (MongoDB)
• tls=true&tlsCAFile=... - Required for DocumentDB

AWS DocumentDB Configuration

DocumentDB requires change streams to be enabled at the collection level:

# Enable change streams (requires admin privileges)
db.adminCommand({
  modifyChangeStreams: 1,
  database: "test",
  collection: "users",
  enable: true
})

Or set allow_modify_change_streams: true in tap config to auto-enable.

Idle Timeout Behavior

The tap automatically exits after 10 seconds of inactivity:

• No manual intervention needed - No Ctrl+C required
• Production-ready - Safe for automated pipelines
• Resource-efficient - Doesn't hang indefinitely
• Preserves resume tokens - Can resume from exact position

Switching Between Modes

From INCREMENTAL to LOG_BASED:

1. Ensure MongoDB is running as replica set
2. Update connection string to include ?replicaSet=rs0
3. Clear existing state: rm -rf .meltano/extractors/tap-mongodb/
4. Use tap-mongodb-cdc plugin or update metadata to LOG_BASED

From LOG_BASED to INCREMENTAL:

1. Update connection string (can remove replica set parameters)
2. Clear existing state
3. Use base tap-mongodb plugin or update metadata to INCREMENTAL

Troubleshooting

"Change streams not available"

• Ensure you're connecting to a replica set with ?replicaSet=rs0
• For DocumentDB, verify change streams are enabled on collections

"Resume point no longer in oplog"

• The oplog window was exceeded (too much time between syncs)
• Delete state file to start fresh: rm -rf .meltano/
• Consider running syncs more frequently

No events captured

• Ensure changes occurred AFTER establishing the change stream position
• Change streams only capture events after the stream opens
• Run an initial sync first to establish position, then make changes

Cleanup Docker Environment

# Stop and remove containers
docker compose down -v

# Remove generated files
rm -rf output/ .meltano/run/

Additional Resources

• MongoDB Change Streams Documentation
• DocumentDB Change Streams Guide
• Testing helpers: docker/seed-cdc-test-data.py
• Docker setup: compose.yml (3-node replica set)

Developer Resources

Follow these instructions to contribute to this project.

Initialize your Development Environment

uv sync

Create and Run Tests

Create tests within the tap_mongodb/tests subfolder and then run:

uv run pytest

You can also test the tap-mongodb CLI interface directly using uv run:

uv run tap-mongodb --help

Testing with Meltano

Note: This tap will work in any Singer environment and does not require Meltano. Examples here are for convenience and to streamline end-to-end orchestration scenarios.

Next, install Meltano (if you haven't already) and any needed plugins:

# Install meltano
uv tool install meltano

Now you can test and orchestrate using Meltano:

# Test invocation:
meltano invoke tap-mongodb --version

# OR run a test EL pipeline:
meltano run tap-mongodb target-jsonl

SDK Dev Guide

See the dev guide for more instructions on how to use the SDK to develop your own taps and targets.