Database connector

The MongoDB data catalog your whole team can trust.

The Dawiso MongoDB data catalog turns every cluster, database and collection into a searchable inventory, with field-level documentation alongside relational and BI sources.

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Live connector Stable connector

MongoDB

Dawiso

Metadata-only · your data never leaves the source

Type: Document database
Auth: Username & password (read-any-database role)
Sync: Scheduled, incremental
Direction: Read-only · metadata

First things first

What is a data connector?

Metadata-only Read-only access Incremental sync Cross-system lineage

A data connector is the bridge between a tool in your stack and the catalog that gives you a unified view of it. Once a connector is configured, it reaches into the source system on a schedule, reads out the metadata - schemas, tables, dashboards, jobs, ownership, lineage - and represents it inside the catalog. Your actual rows and values stay where they are.

Connectors are the reason a data catalog can answer questions like "which Power BI dashboard depends on this Snowflake table?" or "who owns the orders topic in Kafka?" - automatically, without anyone keeping a spreadsheet up to date.

Three properties separate a good connector from a brittle one: it should be read-only and safe, it should be incremental so a full re-scan isn't required for every refresh, and it should resolve lineage across system boundaries, not just inside one tool.

About the platform

What is MongoDB?

MongoDB is the document database built for unstructured, JSON-shaped data. Web and mobile teams use it as their operational backbone, and the managed Atlas service is the dominant cloud deployment. As of 2024, MongoDB reports 50,000 customers; Atlas alone drives 70% of company revenue.

MongoDB stores collections with flexible schemas, which is a feature for developers and a problem for governance. There's no information_schema to read, no native lineage to BI, and no business glossary tying collections to the terms the rest of the company uses. That's where the Dawiso MongoDB data catalog joins the picture: read-only, metadata-only, and cross-platform.

Architecture

How Dawiso connects to MongoDB

A small read-only role on the MongoDB side. The Dawiso scanner pulls metadata on a schedule. Everything ends up in your catalog, business-readable.

Source

MongoDB cluster

Databases & collections
Field paths & types
Indexes & key patterns
Cluster roles & users

REST · JDBC

Dawiso scanner

Read-only metadata

Schema & object discovery
Dependency resolution
SQL flow parsing (optional)
Sampling on opt-in

Internal

Catalog

Dawiso platform

Searchable metadata
Lineage & ownership
Business glossary
Policy & classifications

Connection details

Protocol: MongoDB driver protocol · listDatabases, listCollections, collStats, find
Authentication: Database user with built-in 'Only read any database' role
Lineage: MongoDB does not expose native lineage. Dawiso pulls collection and field metadata and links it to relational and BI catalogs at the data-product layer; field-to-table joins are modelled manually or via dbt source manifests

Setup

Connect MongoDB in 4 steps

01

Whitelist Dawiso IP

In Atlas Network Access, add the Dawiso ingestion server IP (Customer Success provides it). Self-hosted MongoDB: open the firewall to the Dawiso Integration Runtime instead.
02

Create a read-any-database user

In Database Access, add a new user (e.g. dawiso_reader) with password auth. Assign the built-in 'Only read any database' role, or scope a custom role with listDatabases, listCollections, collStats and find.
03

Connect in Dawiso

Provide the hostname (cluster.region.mongodb.net), user and password. Toggle SRV schema or TLS as required and pick an authentication source database if your cluster uses one.
04

Run ingestion

Pick the databases to scan as a comma-separated list. Schema is sampled per collection; scheduled incremental sync keeps the catalog current.

Capabilities

What you get with the MongoDB connector

Collection & field catalog

Every MongoDB database, collection and indexed field is searchable. Inferred field types, owners, and links to the related dbt models for downstream BI.
Cross-platform lineage

Link MongoDB collections to the warehouse landing tables and Power BI reports that consume them, so business has end-to-end visibility despite the document model.
PII classification

Classify a field once. Dawiso flags every MongoDB document field carrying email, IBAN or government IDs across every database and cluster.
Ownership & certification

Mark collections as certified, deprecated or under review. Owners are visible in the catalog alongside the Atlas project and database user.
Business glossary alignment

Tie MongoDB collections and field paths to glossary terms so 'customer.email' has the same definition as the ERP customer table.
Read-only by design

Dawiso reads metadata through a user with read-only role: listDatabases, listCollections, collStats and find. No write privileges anywhere.

Business value

Why teams turn on the MongoDB connector

−65%
Fewer 'where is that field?' pings

Developers find the certified MongoDB collection in Dawiso instead of asking which cluster holds the customer profile schema.
End-to-end
Lineage past the document boundary

See how MongoDB collections feed the warehouse, the data product and Power BI, in one cross-platform view. Manual hand-offs disappear.
Audit-ready
GDPR & DORA evidence

Sensitive MongoDB fields are classified once, the policy follows them downstream into structured stores, with a full audit trail.

Ready to catalog your MongoDB?

Set up the connector in an afternoon. See your first lineage graph the same day.

Read the docs

Frequently asked questions

Still curious? Talk to our team ->

How is data organized in MongoDB?

MongoDB stores data as collections of JSON-like documents inside databases, with no fixed schema. Dawiso infers and catalogs collection structure read-only - fields, types, owners and lineage - so schemaless data becomes searchable and governed.

Does MongoDB have a data catalog?

No native catalog. Dawiso reads MongoDB metadata read-only and turns databases, collections and inferred field schemas into a searchable catalog with ownership, classification and cross-platform lineage.

What is the purpose of a data catalog?

A data catalog makes every collection discoverable, documented and trustworthy. Dawiso links MongoDB data to the rest of your stack so owners, meaning and lineage are clear to the whole business.

What permissions does Dawiso need in MongoDB?

A database user with the built-in 'Only read any database' role, or a custom role with listDatabases, listCollections, collStats and find. Read-only end to end. Dawiso never writes back to MongoDB.

Does Dawiso copy our MongoDB data?

No. Dawiso reads cluster, database, collection, field and index metadata only. Schema is inferred from a small sample per collection; full-document scans are opt-in per data source and never run automatically.

Atlas, self-hosted, on-premises - which deployments are supported?

All three. Atlas via Dawiso ingestion IP whitelisting in Network Access. Self-hosted in cloud through firewall whitelisting. On-premises through the Dawiso Integration Runtime, which pushes metadata to the Dawiso tenant.

How does field-level lineage work for a schemaless store?

MongoDB does not expose native lineage. Dawiso documents inferred field paths per collection, then links them to relational targets and BI reports through dbt source manifests or manual mapping at the data-product layer.