400+ managed connectors
Marketing, sales, finance, product, and ad platforms - plus databases and flat files - all maintained for you.
Panoply
Data Warehouse
Every source into Panoply, analytics-ready.
Dataddo is the turnkey data layer for Panoply. Connect 400+ business sources, land clean, governed tables with no pipelines to build, and keep your Panoply warehouse ready for analysis and BI. Fully managed - no lock-in.
ARCHITECTURE
Where Panoply 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 Panoply, analytics-ready
Connect 400+ sources and land clean, governed tables in Panoply - no pipelines to build, and no bad or broken data slipping through.
ETL, ELT, CDC, streaming
Load Panoply 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 Panoply 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 Panoply.
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 Panoply tables.
WITH VS. WITHOUT
Who carries the load when things change upstream
Keep the same sources flowing into Panoply - 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 Panoply 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 Panoply |
| Endpoint deprecated | You re-engineer the integration. | We own the update - the data contract holds. | Your Panoply 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 Panoply |
| Silent degradation | You find out when a report or model run fails. | Proactive monitoring catches anomalies and delays first. | Issues caught before Panoply 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 Panoply
The delivery pattern changes, the platform does not. Load Panoply 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 Panoply for BI and reporting, Load raw data into Panoply 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 Panoply in near real time, Keep Panoply 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 Panoply for real-time analytics, Keep Panoply 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 Panoply into CRMs and ad platforms, Operationalize Panoply 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
Panoply + Dataddo, answered
What can I load into Panoply?
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 Panoply.
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 Panoply?
Through an authorization certificate configured in the Dataddo authorizer, after which Dataddo validates the connection. Data loads into the Project and Dataset hierarchy you select.
What access does Dataddo need for Panoply?
The database user needs rights to create tables and to insert, update and delete rows, Panoply must be reachable by Dataddo, and the Dataddo IP ranges must be allowed behind a firewall (SSH tunneling is supported).
What are Panoply table-naming rules in Dataddo?
Panoply table names may contain only letters, numbers, dashes or underscores. Missing tables are created automatically on the first write and date tokens such as {{1d1}} are supported.
Can I send data back out of Panoply?
Yes. Dataddo does reverse ETL - push modeled metrics and segments from Panoply 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 Panoply 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 Panoply tables you own, and pipelines are warehouse-agnostic - you can add or switch warehouses without rebuilding your sources.