Enterprise-Grade Data Governance

Track Your Data From Source to Insight

Lakehouse lineage tracking with automated DQ gates and comprehensive audit evidence hub. Ensure data quality, compliance, and full traceability across your entire data ecosystem.

Complete Lineage Solution

Everything you need to track, validate, and audit your data pipelines in one unified platform.

🔗

End-to-End Lineage

Automatic discovery and visualization of data flow from source systems through transformations to final consumption points.

🛡️

DQ Gates

Configurable data quality checkpoints that validate data integrity at every stage of your pipeline with automatic alerts.

📋

Audit Evidence Hub

Centralized repository of all data transformations, access logs, and compliance evidence for regulatory requirements.

Real-Time Tracking

Monitor data movements in real-time with instant notifications on anomalies, failures, or quality degradation.

🏗️

Lakehouse Native

Built for modern data lakehouse architectures with native support for Delta Lake, Apache Iceberg, and Hudi.

🔌

Universal Connectors

Pre-built integrations with major data platforms, warehouses, ETL tools, and BI systems out of the box.

How It Works

Four simple steps to complete data lineage visibility.

1

Connect

Link your data sources, pipelines, and destinations with our universal connectors.

2

Discover

Automatic crawling and mapping of all data assets and their relationships.

3

Monitor

Set up DQ gates and real-time monitoring for continuous data health tracking.

4

Govern

Generate audit reports, track compliance, and maintain complete evidence trails.

99.9%
Lineage Accuracy
<50ms
Query Latency
500+
Pre-built Connectors
100%
Audit Coverage

Simple API, Powerful Results

Integrate lineage tracking with just a few lines of code.

lineage_config.py
from datalineage import LineageClient, DQGate

# Initialize the lineage tracker
client = LineageClient(
    api_key="your-api-key",
    environment="production"
)

# Define a data quality gate
dq_gate = DQGate(
    name="customer_validation",
    rules=[
        {"field": "email", "check": "not_null"},
        {"field": "created_at", "check": "valid_date"}
    ]
)

# Track transformation with audit evidence
with client.track("etl_customer_pipeline") as lineage:
    lineage.add_source("raw.customers")
    lineage.apply_gate(dq_gate)
    lineage.add_target("curated.customers")

Built for Scale

Data Sources

Databases, APIs, Files, Streams

Ingestion Layer

Kafka, Spark, Airflow

Storage Layer

Delta Lake, Iceberg, Hudi

DataLineage.tech Platform

Lineage Tracking • DQ Gates • Audit Hub • Compliance Engine

Analytics

BI Tools, ML Platforms

Governance

Catalogs, Access Control

Compliance

Reports, Audits, Evidence

Ready to Transform Your Data Governance?

Start tracking your data lineage today. Free trial includes full platform access.