Microsoft OneDrive Microsoft OneDrive

Microsoft OneDrive

Object Storage & Data Lake

Dataddo is the turnkey data layer for Microsoft OneDrive. Deliver governed data from 400+ business sources to OneDrive as Parquet, CSV, JSON, or JSONL - partitioned and on your schedule - so your teams get analysis-ready files right where they already work. No pipelines to build.

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Book a Demo Read the docs Use Microsoft OneDrive as a source instead
ARCHITECTURE

Where Microsoft OneDrive fits in your data architecture

Sources

Business / DB / File / Streaming Connectors

450+ available, any direction

Orchestration

Monitoring

Governance & Lineage

IAM & SSO

Dataddo Platform

Speed Security Governance
Control Plane
Data Plane

Destinations

DWH / Data Lake / Lakehouse

Consumption

AI & Agents / Analytics

ETLELTReverse ETLCDCData Streaming
Any direction, any workload
OPEN FORMATS & PARTITIONING

Land Microsoft OneDrive data in open formats, partitioned for query

Every flow run writes governed data to Microsoft OneDrive as an open file - columnar Parquet for analytics, or row-based CSV, JSON, and JSONL for interchange - laid out in date-based partitions so engines like Athena, Trino, BigQuery, and Spark read it as a clean dataset and scan only what they need.

Parquet, CSV, JSON, and JSONL

Write to Microsoft OneDrive in the format your engine expects - compact, columnar Parquet for fast analytics on Athena, Trino, Spark, and BigQuery, plus row-based CSV, JSON, and JSONL for interchange any tool can read.

400+ managed connectors

Marketing, sales, finance, product, and ad platforms - plus databases and flat files - all maintained for you and ready to land in Microsoft OneDrive out of the box.

Date-partitioned datasets

Each run lands as its own dated file, so Microsoft OneDrive is organized as a partitioned dataset and query engines prune to just the files they need.

Snapshot or latest-state

Keep every run as a dated snapshot, or keep only the latest file - the file-naming strategy is your state management, chosen per flow.

Load the full history

Backfill historical date ranges into Microsoft OneDrive on demand - seed a new lake with everything you have, or reload a range to fill a gap.

Clean, governed data

Blend and reshape sources, then let the Data Quality Firewall stop bad records and PII detection mask sensitive fields before anything lands in Microsoft OneDrive.

WITH VS. WITHOUT

Who carries the load when things change upstream

Keep the same sources flowing into Microsoft OneDrive - and see who owns it when an API, schema, or endpoint changes:

Without Dataddo With Dataddo Outcome for you
API or auth change You discover the breakage and scramble to fix it. We update the connector and restore the pipeline - often before you notice. Files keep landing in Microsoft OneDrive
Schema drift Columns change and pipelines break or corrupt data silently. Detected automatically and handled by configurable rules. Only clean data lands in Microsoft OneDrive
Endpoint deprecated You re-engineer the integration. We own the update - the data contract holds. Your Microsoft OneDrive loads keep working
Missing connector You build and maintain a custom integration. We build it and maintain it, under a ~4-week SLA. Any source can reach Microsoft OneDrive
Silent degradation You find out when a report or model run fails. Proactive monitoring catches anomalies and delays first. Issues caught before your lake reads bad files
Debugging You dig through logs across disconnected tools. Run histories, payload inspection, and end-to-end lineage in one place. Faster root-cause, less downtime
USE CASES

What data teams build on Microsoft OneDrive

A data lake earns its keep when it feeds real work. Here are common ways teams put Microsoft OneDrive to use, and the Dataddo connectors that keep each one supplied - all landed in open formats, on your schedule.

Unify marketing and advertising data

Land campaign, spend, and web-analytics data from every channel into Microsoft OneDrive for attribution, reporting, and marketing-mix modeling across tools.

Google Ads Facebook Ads Google Analytics 4 YouTube Analytics + 400 more

Offload databases for analytics

Replicate operational databases into Microsoft OneDrive so heavy analytical and historical queries run on the lake instead of your production systems.

PostgreSQL MySQL SQL Server Oracle MongoDB + 400 more

Feed data science, ML, and AI

Land large, raw datasets as Parquet for feature engineering, model training, and notebook exploration with Spark, pandas, or your ML stack.

PostgreSQL MongoDB Kafka Salesforce + 400 more

Archive raw data at low cost

Keep a cheap, long-term history of SaaS, CRM, and finance data in open formats for compliance and audit, without warehouse storage bills.

Salesforce HubSpot NetSuite Stripe + 400 more
Case Studies

See what data teams build with Dataddo

65,000 Social Media Accounts. One Platform. Zero Manual Authorizations.

65,000 Social Media Accounts. One Platform. Zero Manual Authorizations.

One of the world's largest beauty and consumer goods companies, operating across hundreds of markets and managing one of the most complex social media data estates in the industry.

Beauty & Consumer Goods

 How Livesport Activates Data, Saves Engineering Resources with BigQuery and Dataddo

How Livesport Activates Data, Saves Engineering Resources with BigQuery and Dataddo

Livesport is a global provider of real-time sports statistics, news, and other sports information.

Entertainment

 How ID&T Group Activates Data from 1M+ Festival Fans and Dozens of Social Accounts

How ID&T Group Activates Data from 1M+ Festival Fans and Dozens of Social Accounts

ID&T is the world's pioneering electronic music entertainment company, known for organizing major electronic music festivals such as Defqon.1, Awakenings, and Mysteryland.

Entertainment

 How Sensire Accelerated Migration of a Proprietary On-Premise Data Infrastructure to the Cloud with Dataddo

How Sensire Accelerated Migration of a Proprietary On-Premise Data Infrastructure to the Cloud with Dataddo

Sensire is a large healthcare organization that provides care to clients in their own homes, as well as in nursing facilities.

Healthcare

 How Ringside.ai Builds a Data Product Better and Faster Using Dataddo

How Ringside.ai Builds a Data Product Better and Faster Using Dataddo

Ringside.ai provides a marketing data platform that specializes in analytics and attribution.

Marketing

 How Publicis Groupe Brasil Uses Dataddo's API to Scale a Data Product

How Publicis Groupe Brasil Uses Dataddo's API to Scale a Data Product

Publicis Groupe Brasil is the Brazilian branch of Publicis Groupe, the second largest communications group in the world, with over 1,500 employees across nine subsidiaries including Leo Burnett, Performics, and Publicis Brasil.

Advertising
FAQ

Microsoft OneDrive + Dataddo, answered

What file formats can Dataddo write to Microsoft OneDrive?

Parquet, CSV, JSON, and JSONL. Each flow run writes a file in the format you pick, with format-level controls - CSV delimiter, header, and date format, or the timestamp unit for Parquet, JSON, and JSONL.

How does partitioning work?

Each flow run lands as its own dated file, so Microsoft OneDrive is organized as a date-partitioned dataset. Query engines then read only the partitions they need instead of scanning everything, which keeps queries fast and costs predictable.

How does Dataddo write to Microsoft OneDrive?

Dataddo writes files to your OneDrive folder on the schedule you set, in Parquet, CSV, JSON, or JSONL. Dynamic, date-based file naming keeps each run as its own file, so you can build a partitioned history or refresh a single latest file.

Can Dataddo append or replace files?

Yes. Insert keeps writing new files, and create-new-or-replace overwrites the file at the same name. For lakehouse table formats like Apache Iceberg, Dataddo applies warehouse-style write modes to the table itself.

How is my data secured?

Dataddo is SOC 2 Type II and ISO 27001 certified. Data is encrypted in transit and at rest, PII can be masked or hashed, and EU or US data residency is available. You connect Microsoft OneDrive with your own keys or an assumed role.

Will this run up my storage bill?

Incremental loads write only new or changed data, and columnar Parquet compresses well - so you store and scan less. You control the schedule and the partition layout, which keeps storage and query costs predictable.

Am I locked in?

No. Data lands in open file formats in a bucket you own, and pipelines are storage-agnostic - you can add or switch object stores, or point the same sources at a warehouse, without rebuilding anything.