Solutions / Dagen for AWS / Modernize / Oracle & Teradata

Dagen for AWS · Modernize

Modernize your Oracle and Teradata warehouse on AWS, starting from the logic you already have.

Dagen maps the estate you already run, lands pipelines on Iceberg on S3 in your AWS account, and serves Agent Views over MCP on the engines you already own.

The pain

The appliance, the license, and the logic are welded together.

Hardware refreshes, per-core licensing, and ETL renewals are coupled, so no single cost can come down without moving the whole warehouse, and a renewal sets the deadline.

Dagen for AWS fits Oracle, SQL Server, Teradata, or warehouse estates headed to commercial AWS.

Day 0 · Iceberg migration

Day 0: land on Iceberg.

A warehouse migration starts with the map. Dagen reads tables, views, pipelines, and legacy ETL and builds live lineage and dependencies.

You choose the landing target, or Dagen’s agent recommends one. On AWS, the open destination is Iceberg on S3, and Snowflake can stay for the workloads that belong there.

Day 1 · ETL modernization

Day 1: modernize the ETL on AWS Glue.

Day 1 runs the modernized ETL on AWS Glue, in your AWS account.

Dagen’s agents read the pipelines and logic you already have, and that logic is carried forward into Iceberg-native jobs.

  • EMR Serverless when the jobs need Spark at scale.
  • Snowpark where Snowflake stays.
Day 2 · Data foundation for AI agents

Day 2: a data foundation for AI agents.

Dagen is the data control plane for AI. Policy travels with the data: row- and column-level permissions apply before an agent ever sees a record.

Agent Views are governed, machine-readable views with definitions, access, and lineage attached, served over MCP to the apps and agents that use them.

Deeper product: data control plane · MCP.

AWS-native

Iceberg on S3. Your account. Your IAM.

Dagen deploys in your AWS account under your IAM and networking, and your data stays in your S3.

More on Dagen for AWS.

Proof

From legacy banking data to AI-ready infrastructure.

See how Dagen helped modernize a banking data warehouse, turning legacy ETL into modern pipelines on Apache Iceberg and AWS.

FAQ

Oracle and Teradata on AWS, answered.

Is Iceberg on S3 a rip-and-replace of our warehouse?+

No. Iceberg on S3 is the open destination layer on AWS, not a rip-and-replace warehouse move. Warehouses can stay for the workloads that belong there.

Does data leave our AWS account?+

No. Dagen deploys in your AWS account under your IAM and networking, and your data stays in your S3.

What does a first workload look like?+

Start with a single Oracle or warehouse path to Iceberg on S3. You get a migrated pipeline, not a restaffed rebuild.

Bring one Oracle or Teradata path to a technical demo.

We’ll walk through one path to Iceberg on S3, on the AWS account you already run.