M-Files connector

Set up the M-Files connector in Kaivo: authentication, configuration, the BigQuery tables it syncs, and answers to common questions.

Written By Lauri Raivio

Last updated About 4 hours ago

Kaivo is a fully managed data platform that syncs your M-Files data into a Google BigQuery warehouse and keeps it up to date automatically. There is no pipeline to build and no infrastructure to run, so you can spend your time analysing your data from M-Files instead of moving it.

What is the M-Files connector

Sync your M-Files documents and metadata into BigQuery with Kaivo to report on the content your team manages alongside the rest of your data.

CategoryFiles & Databases
StatusGenerally available
AuthenticationUsername and password
SetupSelf-service

Getting started with the M-Files connector

  1. Sign up for Kaivo and create a workspace.
  2. Connect your M-Files account.
  3. Choose which tables to sync.
  4. Wait for the initial sync to finish.
  5. Query your data in BigQuery or your favourite AI or BI tool.

Authenticating M-Files

Connect with your M-Files login. You provide:

FieldDescription
Password

Configuring the M-Files connector

When you set up the connector, you provide:

FieldDescription
Username
Vault GUID
Server URL
Object Type

Built-in object types are document (0), document collection (9), assignment (10), share (19), email (20), and email conversation (21). There may also exist custom types that are not listed here. In most cases, files are associated with documents, and this should be zero.

Object ID

The ID of an object is found on the M-Files user interface.

Tables and columns synced from M-Files

The streams and columns for this connector aren't listed automatically yet.

How the M-Files sync works

After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where M-Files supports it, each sync pulls only new and changed records so it stays fast; otherwise it refreshes the whole table. Every record keeps its original ID, so you won't get duplicate rows.

Frequently asked questions

How long does the initial sync take for M-Files?

It depends on how much history is in your M-Files account. Most initial syncs finish within minutes, while large accounts can take a few hours. After that, syncs only fetch new and changed records, so they're much faster.

Can I sync only some tables or columns?

Yes. You pick which tables to sync when you set up the connection and can change the selection later. Tables you don't select are never copied to your warehouse.

What happens when M-Files's schema changes?

New fields are never added automatically. You choose which fields to sync, so data you haven't selected (sensitive personal data, for example) never lands in your warehouse. When a new field appears, it becomes available for you to add. What happens to removed or renamed fields depends on a table's sync mode: full-refresh tables always match what's currently in M-Files, so dropped fields disappear, while incremental tables keep their existing columns and history, so an old field stays and newly added fields fill in over time.

How do I handle GDPR or data deletion requests?

Your data lives in your own Kaivo-managed BigQuery warehouse, so the most direct option is to delete or anonymise specific records right in BigQuery. If you delete data in M-Files instead, full-refresh tables drop it on the next sync, while incremental tables keep it, so you would remove the row in BigQuery or ask us to run a full refresh. To remove everything, delete the M-Files connector in Kaivo and all of its synced data is deleted with it.

Common use cases for M-Files data

Document reporting

Turn the documents and metadata you manage in M-Files into dashboards and metrics.

Process tracking

Analyse document status and workflow data to monitor approvals and bottlenecks.

Combine with other sources

Join M-Files metadata with your other systems in BigQuery for a full view.

Keep a synced history to see how your content and processes change over time.

Use M-Files data in your AI and BI tools

Once M-Files data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools or any BI tool that connects to BigQuery. Here's how the most common destinations work with M-Files data.

Claude

Use Kaivo's MCP server to give Claude secure, workspace-scoped access to your data. Setup guide →

Power BI

Microsoft's BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide →

Data Studio

Free Google BI tool with native BigQuery support. One-click connection to your Kaivo warehouse; great for SMB teams on Google Workspace. Setup guide →

Tableau

The premium analytics standard, with native BigQuery integration. Setup guide →

Google Sheets

Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide →

Excel

Connect via Power Query's BigQuery connector. Setup guide →

Metabase

Open-source BI tool with strong BigQuery support. Setup guide →

See our pricing page for M-Files connector pricing and plan details.