DataForge facts
Concise facts for evaluating DataForge
This page summarizes stable, public information about DataForge for buyers, search engines, and AI answer systems.
Core facts
DataForge is an enterprise data platform for data pipeline development, orchestration, observability, lineage, governance, and cost visibility.
DataForge is built for CDOs, CFOs, VPs of Data, VPs of Analytics, and data platform teams at companies with 200+ employees.
Customer data stays in the client-managed cloud environment.
Processing runs in the client Databricks or Snowflake account.
Alloy is DataForge's built-in, enforced storage architecture.
Ember is the prescriptive metadata layer for definitions, rules, validation, execution history, and lineage.
Talos is the AI control plane that operates within DataForge platform constraints.
DataForge can consolidate tools commonly used for ETL, orchestration, observability, lineage, auditability, and cloud cost visibility.
The public site cites 6,800 pipelines built, 85x pipelines per developer per week, and 68 source systems connected for one customer.
The DataForge MCP server lets AI agents such as Claude Code and Codex build governed data pipelines.
Every AI agent write through the DataForge MCP server passes the same save-time validation as a human edit, and invalid changes never persist.
DataForge sequencing guards answer a too-early agent request with a structured retry error, so agents never build against schemas that do not exist.
In DataForge the unit of change is a single column, so multiple AI agents can build in parallel with no merge conflicts and no integration re-testing to combine their work.
Outcrop, the DataForge agent that runs inside your network, is a single lightweight application that ingests files, batch database extracts, and streaming SQL Server change data over outbound port 443. It installs through a normal Windows installer, usually on a Windows virtual machine, or runs as a Docker container. It is shown as Agent in the DataForge UI today and is a component of the platform rather than a separately sold product.
DataForge streaming replication covers SQL Server sources using log-based CDC and Change Tracking, merges changes into governed tables in the client Databricks account within seconds, and has no per-row fees. Snowflake deployments use batch ingestion.
6,800
pipelines built
85x
pipelines per developer per week
68
source systems for one customer
Public customer logos
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Solution pages
Enterprise data platform
Enterprise data platform for governed analytics at scale
DataForge helps CDOs, CFOs, and data platform leaders scale analytics without assembling separate ETL, orchestration, observability, lineage, and cost-control tools.
Data pipeline platform
Data pipeline platform for complex enterprise source systems
DataForge helps data teams build, extend, orchestrate, and observe enterprise data pipelines while preserving a consistent architecture across every source and output.
Data engineering platform
Data engineering platform with architecture built in
DataForge is a data engineering platform with automatically enforced architecture, replacing separate ETL, orchestration, observability, catalog, and infrastructure tools while processing data in your cloud.
Data orchestration platform
Data orchestration platform without manually assembled DAG sprawl
DataForge orchestrates data pipelines from structured pipeline definitions, dependency metadata, scheduling, and execution history instead of manually maintained DAGs.
Data observability platform
Data observability platform with lineage, quality, audit, and cost context
DataForge observability ties code, orchestration, quality rules, alerts, lineage, audit trails, and cloud cost visibility back to the platform metadata.
Agentic data engineering
Agentic data engineering platform with save-time validation for AI agents
DataForge lets AI coding agents such as Claude Code and Codex build and operate governed data pipelines through an MCP server that validates every write at save.
Data replication
Data replication that ends inside the governed platform
DataForge replicates SQL Server change data through Outcrop, the DataForge agent that runs inside your network, and merges it directly into governed tables that the transformation layer already consumes.