400+ managed connectors
Marketing, sales, finance, product, and ad platforms - plus databases and flat files - all maintained for you.
Amazon Redshift
Amazon Redshift
Data WarehouseDataddo is the turnkey data layer for Amazon Redshift. Connect 400+ business sources, land clean, governed tables with no pipelines to build, and activate Redshift data across your AWS stack and operational tools. Fully managed - no lock-in.
ARCHITECTURE
Where Amazon Redshift 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 Amazon Redshift, analytics-ready
Connect 400+ sources and land clean, governed tables in Amazon Redshift - no pipelines to build, and no bad or broken data slipping through.
ETL, ELT, CDC, streaming
Load Amazon Redshift 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 Amazon Redshift 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 Amazon Redshift.
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 Amazon Redshift tables.
WITH VS. WITHOUT
Who carries the load when things change upstream
Keep the same sources flowing into Amazon Redshift - 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 Amazon Redshift 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 Amazon Redshift |
| Endpoint deprecated | You re-engineer the integration. | We own the update - the data contract holds. | Your Amazon Redshift 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 Amazon Redshift |
| Silent degradation | You find out when a report or model run fails. | Proactive monitoring catches anomalies and delays first. | Issues caught before Amazon Redshift 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 Amazon Redshift
The delivery pattern changes, the platform does not. Load Amazon Redshift 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 Amazon Redshift for BI and reporting, Load raw data into Amazon Redshift 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 Amazon Redshift in near real time, Keep Amazon Redshift 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 Amazon Redshift for real-time analytics, Keep Amazon Redshift 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 Amazon Redshift into CRMs and ad platforms, Operationalize Amazon Redshift 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
Amazon Redshift + Dataddo, answered
What can I load into Amazon Redshift?
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 Amazon Redshift.
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.
What does Dataddo need to connect to an Amazon Redshift cluster?
A Redshift database user (username and password) with rights to create tables and to insert, update and delete rows, plus the cluster hostname, database name and port (default 5439).
How do I let Dataddo reach a Redshift cluster behind a firewall?
Whitelist the Dataddo IP ranges (docs.dataddo.com/docs/network-acl) or connect through the SSH-tunnel option for clusters that are not directly reachable.
Does Dataddo stage data through S3 to load Redshift?
No. Dataddo writes directly to native cluster tables using seven write modes (insert, insert_ignore, truncate_insert, upsert, update, update_ignore, delete); there is no intermediate S3 staging step. Table names may contain letters, numbers, underscores and dashes.
Can I send data back out of Amazon Redshift?
Yes. Dataddo does reverse ETL - push modeled metrics and segments from Amazon Redshift 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 Amazon Redshift 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 Amazon Redshift tables you own, and pipelines are warehouse-agnostic - you can add or switch warehouses without rebuilding your sources.