Data observability platform
Data observability platform with lineage, quality, audit, and cost context
DataForge gives teams observability that is built into the data platform rather than bolted on after pipelines are already running.
Direct answers for evaluation
What is DataForge?
DataForge is a data observability platform for teams that need lineage, quality checks, operational history, auditability, and cloud cost context tied to pipeline definitions.
Who is DataForge for?
DataForge fits data leaders, finance leaders, governance teams, and platform operators who need to trust and explain enterprise analytics pipelines.
What tools does DataForge replace?
DataForge can reduce dependence on separate data quality, lineage, monitoring, alerting, audit reporting, and cost visibility tools.
Where does customer data run?
Observability metadata is tied to workloads running in the client Databricks or Snowflake account while customer data remains in the client-managed cloud.
When should a CDO, CFO, or VP of Data evaluate DataForge?
Evaluate DataForge when data issues are slow to diagnose, lineage is incomplete, quality rules are disconnected, or finance needs better visibility into cloud data platform costs.
Built-in architecture
Alloy gives every pipeline a consistent, enforced layer model so platform complexity does not grow through one-off patterns.
Client-managed cloud
DataForge is positioned for enterprise teams that need customer data to remain in their own cloud environment.
Platform consolidation
DataForge combines pipeline development, orchestration, observability, lineage, auditability, and cost visibility.
Published proof point
The observability product page describes queryable code metadata, quality rules, alerts, lineage, audit trails, and cost visibility.
Evaluate DataForge for your platform
Talk with DataForge about your current data stack, cloud environment, pipeline growth, and executive platform goals.
Talk to us