400+ managed connectors
Marketing, sales, finance, product, and ad platforms - plus databases and flat files - all maintained for you.
Google BigQuery
Data Warehouse
Every source into Google BigQuery, analytics-ready.
Dataddo is the turnkey data layer for Google BigQuery. Connect 400+ business sources, land clean, governed tables with no pipelines to build, and activate BigQuery data back in GA4, Google Ads, and your operational tools. Fully managed and serverless-friendly - no lock-in.
ARCHITECTURE
Where Google BigQuery fits in your data architecture
Sources
Business / DB / File / Streaming Connectors
450+ available, any direction
HubSpot
Google Ads
Google Sheets
Salesforce
SAP S/4HANA
Oracle
Microsoft Dynamics 365
AWS S3
Azure SQL
Google Cloud SQL
MySQL
PostgreSQL
IBM Db2
+ any other
Your existing stack
Orchestration
Monitoring
Governance & Lineage
IAM & SSO
Dataddo Platform
Speed
Security
Governance
Control Plane
UI
Visual workspace for teams to build, run and monitor pipelines
API
Programmatic interface to embed Dataddo in your own stack and workflows
MCP
Dedicated interface for AI & agents to access governed data in context
Data Plane
Isolated deployment
Hyperscalers
AWSAzureGoogle Cloud
Isolated deployment
EU Cloud Providers
HetznerOVHcloudSTACKIT
Isolated deployment
On-Prem
KubernetesOpenShift
Data + Metadata
Destinations
DWH / Data Lake / Lakehouse
Snowflake
Databricks
Microsoft Fabric
Google BigQuery
Amazon Redshift
Azure Synapse
Oracle
IBM Db2
Universal PostgreSQL
Universal MySQL
+ any other
Data + Metadata
Consumption
AI & Agents / Analytics
Claude
Gemini
OpenAI
Mistral
BottleCap AI
Power BI
Tableau
Looker Studio
Databox
+ any other
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
YOUR DATA FOUNDATION
Every source into Google BigQuery, analytics-ready
Connect 400+ sources and land clean, governed tables in Google BigQuery - no pipelines to build, and no bad or broken data slipping through.
ETL, ELT, CDC, streaming
Load Google BigQuery however the workload demands - batch ETL or ELT, real-time CDC from your databases, or continuous event streaming. One platform, every transport pattern.
Write modes that hit SLAs
Insert, upsert, truncate-insert, or delete - pick the write mode per table. Incremental loads and fast, reliable delivery keep Google BigQuery current and meet your data SLAs.
Clean, safe, analytics-ready
Blend and reshape sources, then let the Data Quality Firewall stop bad records and automatic PII detection mask sensitive fields - so only analytics-ready data lands in Google BigQuery.
Schema-drift handling
When a source changes its fields, Dataddo adapts the pipeline and alerts you instead of breaking the load.
Proactive monitoring
Data-quality checks and delivery alerts catch gaps before they reach your dashboards or Google BigQuery tables.
WITH VS. WITHOUT
Who carries the load when things change upstream
Keep the same sources flowing into Google BigQuery - 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. | Pipelines to Google BigQuery keep flowing |
| Schema drift | Columns change and pipelines break or corrupt data silently. | Detected automatically and handled by configurable rules. | Only clean data lands in Google BigQuery |
| Endpoint deprecated | You re-engineer the integration. | We own the update - the data contract holds. | Your Google BigQuery 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 Google BigQuery |
| Silent degradation | You find out when a report or model run fails. | Proactive monitoring catches anomalies and delays first. | Issues caught before Google BigQuery reports break |
| 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 |
DATA TRANSPORT
Every way to move data into and out of Google BigQuery
The delivery pattern changes, the platform does not. Load Google BigQuery by scheduled batch or in real time, and activate its data back out - all governed the same way.
| Transport type | What it does | Typical connectors | Typical business use cases |
|---|---|---|---|
| ETL & ELT | Classic extract-transform-load, or load-first with in-warehouse transformation. | Centralize SaaS, ad, and CRM data in Google BigQuery for BI and reporting, Load raw data into Google BigQuery and model it in-warehouse with SQL or dbt | |
| Change Data Capture (CDC) | Real-time, low-latency replication that tracks row-level changes as they happen. | Replicate production databases into Google BigQuery in near real time, Keep Google BigQuery in sync with operational systems without full reloads | |
| Data Streaming | Continuous, event-driven pipelines for time-sensitive and AI-ready data workloads. | Stream events and webhooks into Google BigQuery for real-time analytics, Keep Google BigQuery continuously fed so dashboards reflect the latest activity | |
| Reverse ETL | Activate your data: push curated, governed records from your AI agents or warehouse back into CRMs, operational systems, and the frontier apps where your teams act on it. | Push modeled metrics and segments from Google BigQuery into CRMs and ad platforms, Operationalize Google BigQuery data in the tools your teams use every day |
Google Analytics 4
SQL Server
MongoDB
Kafka
Marketo
Case Studies
See what data teams build with Dataddo
65,000 Social Media Accounts. One Platform. Zero Manual Authorizations.
Beauty & Consumer Goods
How Livesport Activates Data, Saves Engineering Resources with BigQuery and Dataddo
Entertainment
How ID&T Group Activates Data from 1M+ Festival Fans and Dozens of Social Accounts
Entertainment
How Sensire Accelerated Migration of a Proprietary On-Premise Data Infrastructure to the Cloud with Dataddo
Healthcare
How Ringside.ai Builds a Data Product Better and Faster Using Dataddo
Marketing
How Publicis Groupe Brasil Uses Dataddo's API to Scale a Data Product
Advertising
FAQ
Google BigQuery + Dataddo, answered
What can I load into Google BigQuery?
Any of Dataddo's 400+ sources - marketing and ad platforms, CRMs, finance tools, databases, and flat files - plus custom sources on request. Data is blended and cleansed before it lands in Google BigQuery.
Do I have to maintain the pipelines?
No. Dataddo is fully managed: we maintain the connectors, adapt to source schema changes, and alert you if anything needs attention. There is no infrastructure for you to run.
How does Dataddo authenticate to Google BigQuery?
Dataddo connects with a Google service account (JSON key upload) or an admin-level OAuth account, then writes into the Google Cloud project and dataset you select. The account needs rights to create tables and to insert, update and delete rows in the target dataset.
Can Dataddo update or deduplicate rows in BigQuery, or only append?
Both. BigQuery loads support seven write modes: insert (append, the default), insert_ignore (append while skipping duplicates), truncate_insert (replace), and upsert, update, update_ignore and delete, which match rows on a composite key of up to four columns.
Are there BigQuery table-naming rules Dataddo enforces?
Yes. BigQuery table names cannot contain whitespace or dashes. Missing tables are created automatically on the first write, and date-range tokens such as {{1d1}} let you write to date-sharded tables.
Can I send data back out of Google BigQuery?
Yes. Dataddo does reverse ETL - push modeled metrics and segments from Google BigQuery into CRMs, ad platforms, spreadsheets, BI tools, and other operational apps.
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.
Will this run up my Google BigQuery bill?
Incremental loads write only new or changed rows, and you control the load schedule - so you move and store only the data you actually need.
Am I locked in?
No. Data lands in native Google BigQuery tables you own, and pipelines are warehouse-agnostic - you can add or switch warehouses without rebuilding your sources.