Trace any table or column at any snapshot or datetime, see exact upstream/downstream impact, investigate breakages with accountability, and generate STTM across every language, SQL dialect, and ETL tool in your enterprise.
Atlas unifies your lineage into one stitched graph, lets teams choose any as-of time, compare snapshots with actionable differences, and move from API response to visual trace without losing JSON context.
Powered by Compass parsers + SQLForge engine + Merlin AI
Enterprises run SAS alongside Python notebooks, PySpark pipelines feeding Snowflake, Informatica workflows loading BigQuery, and Alteryx automations transforming Polars DataFrames. Atlas is the first platform that generates a unified, column-level atlas of data lineage across all of them — in one place.
SAS, Python, PySpark, R, Polars, Scala — plus every SQL dialect and ETL product MigryX supports. One lineage graph for your entire data estate.
Not approximate — deterministic. Custom-built parsers trace every column from raw source to final output with transformation logic preserved.
Automatic Source-to-Target Mapping with transformation details, operation types, and module references — exportable to CSV, JSON, and Excel.
Merlin AI analyzes your lineage graph to surface risks, detect anomalies, prioritize migrations, and answer questions in natural language.
Use Atlas as the foundation to build certified, governed data products with built-in lineage, quality metrics, and full traceability.
Understand your entire legacy landscape before migrating. Atlas shows exactly what exists, what depends on what, and the safest path to modernize.
Atlas accepts code and metadata from programming languages, SQL dialects, ETL products, BI tools, and cloud platforms — and unifies them into a single lineage graph.
Plus mainframe languages (JCL, COBOL, PL/1, RPG/AS400) and stored procedure objects (DDL, Views, UDFs, Triggers)
Your SAS lineage tool can't see Informatica. Your SQL tracer can't read Python. You get fragments, never the full picture.
Teams spend weeks manually building Source-to-Target Mapping spreadsheets that are outdated the moment they're finished.
Without cross-platform lineage, modernization projects miss hidden dependencies and break production pipelines.
Regulators want end-to-end traceability. You can't prove it if your lineage stops at the boundary of each tool.
Atlas traces data flows across programming languages, SQL dialects, and ETL products in a single view with point-in-time controls, snapshot comparisons, and reusable drilldowns.
Trace data from a SAS program through a Python transformation into a Snowflake table — column by column, across language boundaries.
Informatica mappings feeding Databricks notebooks running PySpark that loads BigQuery — Atlas maps every hop.
Every column traced from source to target with transformation logic, operation type, and module reference — deterministic, not approximate.
Choose a snapshot or datetime to render the stitched graph as it existed then, compare two snapshots, and drill into concrete added/removed/changed objects.
Atlas Lineage Graph
Parse SAS, Python, PySpark, R, and Polars to extract dataset reads, writes, joins, aggregations, and column transformations — all mapped to the unified graph.
Column-level lineage from 15+ SQL dialects — stored procedures, views, CTEs, window functions, and vendor-specific extensions parsed natively.
Informatica mappings, Talend jobs, Alteryx workflows, DataStage sequences, SSIS packages, ODI interfaces — all parsed into the same lineage model.
Export lineage and STTM to CSV, JSON, Excel, and interactive HTML reports. Feed data catalogs, governance tools, and compliance workflows.
Atlas generates comprehensive Source-to-Target Mapping automatically — no manual spreadsheets, no consultants. Every column, every transformation, every dependency captured with precision.
Trace exactly how each target column is built from source columns — with join conditions, aggregation logic, CASE expressions, and window functions documented.
Each mapping step is classified: direct copy, type cast, aggregation, join, filter, lookup, pivot, concatenation, calculation — machine-readable and auditable.
Follow data through multiple transformation steps: raw table → staging view → PySpark join → Snowflake mart → Power BI dashboard. Every hop captured.
STTM exports to Excel (multi-sheet), CSV, JSON. Integrate with Collibra, Alation, Atlan, or any data catalog via API or file import.
STTM documentation satisfies SOX, GDPR, CCPA, and BCBS 239 requirements for data lineage traceability. Audit-ready out of the box.
Merlin AI augments parser-generated STTM: filling gaps in dynamic SQL, resolving ambiguous column references, and scoring mapping confidence.
Five stages transform raw source code from any language, dialect, or tool into a unified, queryable lineage graph.
What Atlas Delivers
When a model or KPI drifts, Investigate compares snapshots and lineage context so teams can pinpoint what changed, when it changed, and which upstream objects caused it.
Use Atlas lineage as the foundation for certified, governed data products. Every product comes with built-in traceability, quality metrics, and SLAs from day one.
Prove end-to-end data lineage for GDPR, CCPA, SOX, BCBS 239 — across SAS, SQL, Python, and ETL tools. Generate audit-ready reports in minutes.
Before changing a table or column, quantify downstream blast radius with severity scoring and drill from each impacted object to focused lineage paths.
Feed Collibra, Alation, Atlan, or Unity Catalog with rich, parser-generated lineage metadata that goes far beyond what those tools can extract on their own.
Identify redundant transformations, bottleneck datasets, and unused pipelines across your entire estate. Reduce cloud costs 40–60% through lineage-driven optimization.
Million-dollar programs win when every persona sees clear value: auditors get defensible evidence, engineers get safe change planning, and scientists get rapid root-cause investigation.
Auditors do not buy dashboards. They buy evidence quality, traceability, and control effectiveness. Atlas is designed to produce those artifacts on demand.
Engineers need confidence before changing schemas and pipelines. Atlas reduces production risk by turning unknown dependencies into explicit, testable impacts.
Scientists need to answer “why did this metric/model change?” quickly. Atlas shortens incident triage and supports accountable, explainable decisions.
Most lineage tools only understand SQL or only one ETL platform. Atlas covers everything.
| Capability | Atlas | Typical Tools |
|---|---|---|
| Programming language lineage (SAS, Python, PySpark, R, Polars) | ✓ | ✗ |
| 15+ SQL dialect support with vendor extensions | ✓ | ~ |
| ETL product lineage (Informatica, Talend, Alteryx, DataStage, SSIS) | ✓ | ✗ |
| Cross-platform column-level lineage | ✓ | ✗ |
| Automated STTM generation | ✓ | ✗ |
| Custom parser architecture (deterministic, zero guesswork) | ✓ | ~ |
| Parser-driven analysis with optional AI & natural language querying | ✓ | ✗ |
| On-premise / air-gapped deployment | ✓ | ~ |
| Migration impact analysis across all platforms | ✓ | ✗ |
| Data catalog integration (Collibra, Alation, Atlan) | ✓ | ~ |
✓ Full support ~ Partial / approximate ✗ Not supported
Full deployment behind your firewall with zero data leakage. No cloud egress required. Complete data sovereignty.
Global admins manage all tenants and users; tenant users are scoped to assigned tenants with least-privilege controls for safe self-service.
Run lineage analysis in your CI/CD pipelines. Catch breaking schema changes before they ship to production.
Process millions of code artifacts with distributed parsing. Built for the largest enterprise data estates.
OpenAI, Gemini, AWS Bedrock, Cortex, or custom GenAI backends. Your cloud, your model, your choice.
Dedicated success team with SLAs. White-glove onboarding for complex multi-platform environments.
Send us a sample of your code from any combination of SAS, Python, SQL, or ETL tools. We'll generate a cross-platform lineage atlas with full STTM — so you can see exactly what Atlas delivers.