Your data lake ran smoothly today with 42 of 47 tables refreshed across 8 active sources, maintaining a strong 97.8% pipeline success rate and 94.2% data quality score.
Quality score sits at 94.2%, holding steady throughout the day — validation rules are consistently passing across all core oracle-prod and mysql-analytics tables.
Investigate tomorrow why the email_campaigns pipeline experienced rate limit errors twice today and review whether the API quota needs to be increased.
Set up your data lake in minutes, not months.
Six steps from zero to a fully managed, production-ready data lake — no pipelines to write.
Define Your Data Lake
Enter your lake name, budget, and team tags. Autolake handles the rest.
Connect Your Sources
Pick your database, API, or file source — and start ingesting in clicks.
Curate Your Data
Transform, mask, and prepare analytics-ready datasets with built-in SCD support.
Distribute Everywhere
Share curated data via REST APIs, BI tools, and AI/ML platforms instantly.
Monitor Everything
Track usage, cost, and performance from a single built-in dashboard.
AI: Talk to Your Data
Ask questions in plain English and get instant answers powered by your curated data lake.
85% of data lakes fail. We ensure you're part of the 15%.
Data Governance
Role-based access controls, data masking, and compliance policies — enforced automatically at the lake level.
100% AWS Native
Deploy an entire data lake on AWS with zero infrastructure management. No third-party tooling, no vendor lock-in.
End-to-End Lineage
Trace every record from source to destination. Know exactly where your data came from and where it goes.
Built-in Data Quality
Automated validation rules, anomaly detection, and freshness checks on every pipeline run.
Watch Autolake in Action
See how teams go from raw data to a fully managed lake in under five minutes.
Zero maintenance. Automated schema evolution.
After initial setup, Autolake runs your entire data lake autonomously — scaling, healing, and optimizing without human intervention.
Smart Schema Evolution
Auto-detect schema changes between your source and Glue catalog. Compatible changes migrate automatically — breaking changes pause for review.
Before
After
Pipeline Chaining
Parent-child orchestration up to 5 levels deep. Parallel or sequential execution with circular dependency detection.
Auto-Scaling Pipelines
Glue jobs scale workers dynamically with data volume. No config changes, no capacity planning.
Cost Intelligence
MTD and YTD cost breakdown across ingestion, storage, and query. 12-month trends and KPIs in one dashboard.
$2.4k
MTD Cost
87
Tables
99.3%
Success
Anomaly Detection
Volume, freshness, and pattern anomalies flagged automatically. Schema change timelines and pipeline failure trends at a glance.
And 30+ more autonomous features — from PII detection to self-healing retries.
Built for scale and speed
Connectors
Pre-built integrations for databases, APIs, SaaS, and more.
Setup time
From zero to running data pipeline, fully configured.
Reliability
Enterprise-grade uptime with automatic error recovery.
Frequently asked questions
Ready to accelerate your data strategy?
Join leading companies who trust Autolake to drive their digital transformation and stay ahead in the rapidly evolving tech landscape.