Platform / Vendor and Data Stack Agnostic

Vendor- and Stack-Agnostic by Design. Your Strategy Isn't Held Hostage by Your Tools.

Dataddo is purpose-built to be the integration layer that sits above your data stack - not tied to any single vendor. Whether you run on Snowflake, Databricks, Microsoft Fabric, Google BigQuery, or open standards like Apache Iceberg, Dataddo connects to it.

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Your architecture, your call

Data Warehouse, Data Lake, or Lakehouse - You Decide the Pattern

Dataddo doesn't impose an architecture on you. Land the same governed data in a cloud warehouse for BI, an object-store data lake for cheap large-scale retention, or a lakehouse that unifies both - and change the pattern later without re-engineering a single pipeline.

Cloud data warehouse

Deliver analytics-ready tables to Snowflake, Google BigQuery, Amazon Redshift, Azure Synapse, or Microsoft Fabric for fast SQL and BI.

Snowflake BigQuery Redshift Synapse Fabric

Data lake

Write raw or curated data to object storage on Amazon S3, Azure Blob, or Google Cloud Storage when you need open, low-cost retention at scale.

Amazon S3 Azure Blob Cloud Storage

Lakehouse

Get the best of both with open table formats - Apache Iceberg, Delta Lake, and Apache Hudi - on Databricks or the query engine of your choice.

Databricks Apache Iceberg Delta Lake Apache Hudi
Vendor-lock-in prevention by design

Adopt, Migrate, or Run Multi-Cloud Without Rebuilding Pipelines

Open table formats at the destination are table stakes now. Real freedom is staying open on both ends - free to change what feeds your data in and where it goes out, and to adopt new platforms or migrate off legacy systems without re-engineering the flow between them.

Swap Destinations Freely

Re-point a pipeline at a different warehouse or lake and it just re-routes. Source connections, schedules, and transformations stay untouched.

Multi-Destination Delivery

Deliver one governed dataset to several destinations at once - warehouse for BI, lake for retention, an app for activation - from a single pipeline.

Parallel-Run Migrations

Stand up a new destination alongside the old one and run both until you cut over. Migrate off legacy systems with no big-bang switch and no downtime.

Bidirectional by Design

Move data in with ETL/ELT and back out with reverse ETL through the same layer, so it reaches the operational tools that act on it - not just the warehouse.

No Proprietary Lock-In

Open standards on both ends mean connecting your stack never means adopting someone else's. Leave whenever you want, with your pipelines intact.

Without an open movement layer

  • One vendor owns your storage, transformation, and activation
  • Open formats are advertised, but data gravity keeps you in
  • Switching or adding a vendor means re-engineering pipelines
  • Multi-cloud turns into a migration project, not a configuration

With Dataddo

  • You own the data path - open standards on both ends
  • Swap or add destinations without touching your sources
  • Adopt new platforms or migrate off legacy without rebuilding flows
  • Run multi-cloud, on-premises, and EU-sovereign side by side
Any ecosystem, anywhere it needs to run

Pick Your Cloud - or No Cloud at All

Standardize on a single hyperscaler, spread workloads across several, or keep sensitive data inside your own environment. Dataddo stays neutral, so which vendor and where you deploy remain business decisions, not technical constraints.

Any hyperscaler

Run on AWS, Microsoft Azure, or Google Cloud - one of them, or all three at once - with no rework when priorities shift.

AWS Azure Google Cloud

On-premises data plane

Deploy the data plane inside your own network on Kubernetes, OpenShift, or VMware Tanzu so regulated data never leaves your perimeter.

Kubernetes OpenShift VMware Tanzu

EU sovereign clouds

Satisfy data-residency and digital-sovereignty requirements on European providers such as Hetzner, OVHcloud, and STACKIT.

Hetzner OVHcloud STACKIT

Future-Proof Your Data Stack

See how Dataddo keeps your pipelines portable across vendors. Book a walkthrough with one of our engineers.

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