Step-by-step setup for structured, scalable data onboarding
Welcome to the Easiest Way to Register and Onboard Your Data Lakes
Define Your Data Lake
Start by entering key details about your data lake — including name, budget, team tags, and a description. This helps AutoLake organize, classify, and manage your data assets across teams from the very beginning.
Connect to Any Data Source in Minutes
AutoLake lets you easily connect databases, APIs, files, and SaaS apps to your data lake. Just create your source name, select your source type, and you’re ready to start.
Usage. Cost. Performance. All in One View.
AutoLake’s built-in metrics dashboard gives you full visibility into your data lake activity — from storage usage and ingestion time to pipeline and query costs. Spot trends, monitor budgets, and optimize every step.
Completely Cloud-Native
Built for the Cloud.
AutoLake runs natively on all major cloud providers — giving you full flexibility to deploy, scale, and manage your data lake across AWS, Azure, or Google Cloud without vendor lock-in.
Feature Preview
Most Widely Used Autonomous Features
A preview of some of our most widely used autonomous ingestion features that power intelligent data workflows.
Time Travel
Access historical data states at any point in time with precision versioning and rollback capabilities
Current Snapshot
Real-time view of your data's current state with instant synchronization and monitoring
History View
Complete audit trail of all data changes with detailed logging and compliance tracking
Full Load
Complete data synchronization capabilities with optimized bulk transfer protocols
Incremental Load
Efficient delta-only data updates with change detection and minimal resource usage
Snapshot Load
Point-in-time data capture and loading with consistent state preservation
Auto Pipeline Scaling
Dynamic resource allocation based on demand with intelligent load balancing
Auto Indexing
Intelligent index creation for optimal performance with automated optimization
Custom Scheduling
Flexible scheduling options for data operations with advanced cron and trigger systems
Execution History
Detailed logs and monitoring of all pipeline runs with comprehensive analytics
Data Validation
Automated data quality checks and validation rules with real-time monitoring
Smart Retry Logic
Intelligent failure recovery with exponential backoff and circuit breaker patterns
The traditional data integration model is outdated
Modern data teams need solutions that scale automatically, reduce complexity, and deliver results faster.
Traditional Integration
AutoLake
Frequently Asked Questions
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