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ETL FACTORY

Metadata-driven data integration

Design. Generate. Deliver.

Discover your data landscape with ETL Creator. Define sources, targets, mappings and load strategies once. Let ETL Factory compile that metadata into standardized, production-ready ETL projects for the technology you choose.

See How It WorksExplore the Platform
  • Metadata-Driven
  • Pattern-Based
  • Multi-Engine Architecture
  • Audit Ready
  • Enterprise Focused

ETL Creator

Discover. Model. Define.

Data sources

  • SQL Server
  • Azure SQL
  • Oracle
  • Excel
  • CSV / Flat File

Metadata tree

  • ▸ ERP_PROD
  • ▸ dbo
  • ▾ Customer
  • · CustomerID int
  • · ModifiedDate datetime2

Selected objects

  • DimCustomer · Upsert
  • FactSalesOrder · Watermark

ETL Factory

Compile. Generate. Deliver.

  1. Canonical metadata
  2. Design patterns
  3. Technology adapters
  • SSIS (available)
  • ADF (planned)
  • ODI (planned)
  • INFA (planned)

Delivery

  • DTSX + master
  • ISPAC
  • Audit repository
  • Validation report
Conceptual illustration of the Creator → Factory workflow

The problem

Stop Rebuilding the Same ETL Patterns

Enterprise ETL projects repeatedly solve the same engineering problems: connection setup, metadata discovery, incremental loading, staging, auditing, error handling and deployment structure. ETL Factory turns those repeatable decisions into reusable metadata and design patterns.

Accelerate Delivery

Reduce repetitive package development through metadata-driven generation.

Standardize Engineering

Apply consistent naming, auditing, patterns and project structure.

Multi-Engine by Design

Keep project intent separate from the physical ETL implementation.

Enterprise Governance

Make metadata, decisions and generated artifacts traceable and versionable.

Operational Visibility

Design generated projects with audit and monitoring as first-class concerns.

How it works

From Source Metadata to a Running ETL Project

Six stages carry one project definition from discovery to operation. Creator owns the first two, Factory the next three, and the audit repository closes the loop.

  1. ETL Creator

    Discover

    Connect to permitted customer data sources and explore technical metadata.

  2. ETL Creator

    Design

    Select source objects, target structures, mappings and load requirements.

  3. ETL Factory

    Compile

    Convert project metadata into a technology-independent canonical ETL model.

  4. ETL Factory

    Generate

    Use technology adapters to produce the selected ETL engine's artifacts.

  5. ETL Factory

    Deliver

    Package validated project outputs for the customer's runtime environment.

  6. Audit repository

    Monitor

    Use auditing and operational metadata to provide visibility into ETL execution.

The platform

Two Products. One Automation Platform.

ETL Creator runs close to the customer's data and captures the project definition. ETL Factory stays on the vendor side and compiles that definition into a deliverable ETL project.

ETL Creator

Design Your ETL Project

Customer environment · Windows desktop

ETL Creator runs close to the customer's data environment. It discovers source and target metadata, lets users select objects and define transfer requirements, and produces a standardized project definition without exposing the ETL generation engine.

  • Source and target connection definition
  • Database, schema, table and column discovery
  • Object selection with Dim / Fact classification
  • Mapping configuration and load strategy inputs
  • Watermark and business key metadata
  • Validation before export
  • Mapping workbook, stage DDL and metadata export

ETL Factory

Compile Metadata into ETL Projects

Vendor environment · generation engine

ETL Factory consumes the project metadata, applies reusable engineering patterns and converts the canonical model into technology-specific deliverables through dedicated generator adapters.

  • Metadata validation with rule-coded findings
  • Technology-independent canonical ETL model
  • Design pattern engine
  • Technology adapters
  • Package and master package generation
  • Audit framework generation
  • Static package validation and delivery bundle

Multi-engine architecture

One ETL Definition. Multiple Execution Engines.

ETL Factory separates the logical intent of a data movement project from its physical implementation. The same canonical architecture can be compiled through technology-specific adapters.

Project metadata flows into the canonical ETL model and the pattern engine, then into one adapter per execution engine.
Project metadataCanonical ETL modelPattern engine
SSISAvailable
ADFPlanned
ODIPlanned
INFAPlanned
Available

Microsoft SSIS

The implemented generation path. ETL Factory compiles the canonical model into a complete SSIS project.

Outputs

DTSX packages, master package, project parameters, connection managers, ISPAC

Planned

Azure Data Factory

A dedicated adapter that translates the same canonical model into ADF structures.

Outputs

Pipelines, datasets, linked service definitions

Planned

Oracle Data Integrator

ODI generation from the same project definition and pattern engine.

Outputs

Mappings and load plans

Planned

Informatica

Informatica assets produced from the shared canonical model.

Outputs

Mappings and workflows

Roadmap adapters under evaluation: Microsoft Fabric Data Factory, AWS Glue, Google Cloud Data Fusion. They are not part of the current product.

Design pattern engine

Engineering Decisions, Turned into Reusable Patterns

A load strategy is more than a dropdown. Extraction, staging, change detection, target loading and auditing compose into one generated package flow.

4 of 6 Extraction patterns are generated by the current SSIS adapter.

  • Full Load

    Available

    Truncate target, fast-load the full source.

  • Full Load (Atomic)

    Available

    Load a work table, swap inside one transaction. Target survives a failed read.

  • Incremental Watermark

    Available

    Read rows changed after the last stored watermark.

  • Last X Days

    Available

    Delete and reload a rolling date window.

  • CDC

    Planned

    Read from change data capture tables.

  • Change Tracking

    Planned

    Use SQL Server change tracking versions.

Composed pipeline

Oracle CUSTOMER → DimCustomer

  1. SourceOracle · CUSTOMER
  2. ExtractIncremental Watermark
  3. StageBulk load to work table
  4. DetectBusiness key comparison
  5. LoadSet-based upsert
  6. CloseAudit rows + watermark commit

Source connectivity

Connect to the Data Landscape You Already Have

ETL Creator reads technical metadata from the sources below. Adapter-dependent sources are discoverable but rely on the target engine's provider support at generation time.

  • SQL ServerAvailable
  • Azure SQLAvailable
  • OracleAvailable
  • ExcelAvailable
  • CSV / Flat FileAvailable
  • PostgreSQLAdapter-dependent
  • MySQL / MariaDBAdapter-dependent
  • IBM DB2Adapter-dependent
  • ODBCAdapter-dependent
  • OLE DBAdapter-dependent
  • XMLAdapter-dependent
  • REST APIPlanned

Metadata boundary

Keep Data Access Close to the Customer Environment

ETL Creator runs inside the customer's network and exports technical metadata only. ETL Factory compiles that metadata on the vendor side and returns a generated project.

Customer environment

  1. Source systems
  2. ETL Creator
  3. Technical metadata

ETL Factory environment

  1. Metadata
  2. Compiler + patterns
  3. Generated ETL project
  4. Customer delivery
  • ETL Creator is designed for local metadata discovery inside the customer network.
  • Production dataset rows are not part of the generation contract.
  • Credentials are not embedded in exported project metadata.
  • Generator intellectual property stays separate from customer-side discovery.

Operations

Generation Is Only the Beginning

Every generated package writes to the same audit repository. Execution status, duration, row counts, errors and watermark progress are visible from day one.

Package executionsIllustrative data
PackageStatusDurationRows readRows written
STG_ERP_DIMCUSTOMERSucceeded00:00:4218,204312
STG_ERP_FACTSALESORDERSucceeded00:03:151,204,8809,641
STG_ERP_DIMPRODUCTRunning00:00:194,210—
STG_ERP_DIMSTOREFailed00:00:0700

Available in the audit repository

  • Package status
  • Execution duration
  • Start / end time
  • Rows read, inserted, updated, deleted
  • Error details
  • Watermark progress

Roadmap not yet available

  • Dependency-aware execution
  • Retry policies
  • Error classification
  • Schema drift detection
  • Volume and duration anomalies
  • Controlled remediation

Technical architecture

Built Like a Compiler, Not a Collection of Templates

The canonical model keeps business and integration intent independent from platform-specific implementation. Technology adapters are responsible for translating that intent into the structures required by each target engine.

Generation is deterministic: the same metadata produces the same package identifiers, so generated projects can be diffed, reviewed and versioned like source code.

  1. ETL Creator

    Mapping workbook, stage DDL, metadata scripts

  2. Import

    Excel contract v1 is read into typed records

  3. Canonical model

    Technology-independent project definition

  4. Validation

    Rule-coded checks: project, table, column, pattern, dependency

  5. Pattern compile

    Each table's load pattern becomes a package blueprint

  6. Technology adapter

    Blueprint translated for the selected engine

    • SSIS generator
    • ADF generator · planned
    • ODI generator · planned
    • INFA generator · planned

  7. Static validation

    Generated packages checked before build

  8. Delivery

    Built project, report, manifest and generation history

Engagement

Buy the Project, Not the Engine

Generated customer project artifacts and the ETL Factory generation platform are separate commercial concepts. Most teams start with a delivered project; the engine stays with us.

Project Delivery

For organizations that want generated ETL project artifacts without purchasing the generation engine.

  • Metadata discovery workflow with ETL Creator
  • Project generation
  • Generated deliverables
  • Validation output
  • Technical documentation
Request Project Assessment

Enterprise

For organizations requiring private deployment, governance or custom integration requirements.

  • Private deployment options
  • Governance and standards alignment
  • Custom pattern development
  • Priority engineering support
Contact Sales

Custom

For consulting partners and programs with requirements that do not fit a standard engagement.

  • Scoped together with your team
  • Adapter or pattern extensions
  • Joint delivery planning
Talk to Us

Next step

Build ETL Differently.

From metadata to production-ready integration.

Tell us about your sources and target platform. We will walk through ETL Creator on your metadata and show the project ETL Factory generates from it.

Request a DemoTalk to Us

[email protected]