LakeStack
What is LakeStack?
Lakestack is an AWS-deployed data foundation that connects source systems, transforms and governs data, and makes governed datasets available to analytics tools, applications, operational systems, and AI workloads. It combines data fabric, data pipeline, and data governance capabilities in one platform.
Key Capabilities
- Connects databases, SaaS applications, files, and APIs, including SAP, Oracle, SQL Server, PostgreSQL, MongoDB, Salesforce, HubSpot, Zendesk, and Shopify.
- Supports batch, micro-batch, real-time streaming, and change data capture ingestion.
- Standardizes, models, validates, and enriches data through configurable transformation templates and SQL extensions.
- Maintains centralized business logic, metric definitions, lineage, quality checks, and anomaly detection.
- Applies classification, masking, encryption, anonymization, role-based access controls, and row- and column-level permissions throughout the data lifecycle.
- Exposes governed datasets through SQL-compatible BI tools, versioned REST or GraphQL APIs, reverse ETL, and AI integrations.
- Supports customer 360, dimensional modeling, SCD Type 2 history, funnel analysis, operational dashboards, retrieval-augmented generation, and AI agent workflows.
Audience & Use Cases
Lakestack is designed for data, analytics, engineering, operations, and AI teams that need to consolidate fragmented business data without maintaining separate ingestion, transformation, governance, and activation tools. It supports data modernization, self-service analytics, customer 360 initiatives, real-time operational reporting, governed API access, and AI applications grounded in current business data.
Technical Specifications
Lakestack runs within the customer’s AWS environment. It provides prebuilt source connectors, configurable data transformations, semantic modeling, continuous quality and freshness checks, field-level lineage, auditable activity logs, and domain-based dataspaces. Access policies and masking controls are enforced across analytics, APIs, operational syncs, and AI consumers. The platform integrates with BI tools including Amazon QuickSight, Tableau, Power BI, and Looker, and supports AI services such as Amazon Bedrock, Amazon SageMaker, OpenAI, and Anthropic.
Categories & Use Cases
Product Demos
Technical Details
| Deployment Types | SaaS |
|---|---|
| Mobile Application | No |