Data Lakehouse on Cloud – Next-gen data management beyond lakes and warehouses

Data Lakehouse is a modern data architecture that combines the cost-efficiency and flexibility of data lakes with the reliability and performance features of data warehouses. It offers a unified platform for storing, managing, and analyzing all types of data—structured, semi-structured, and unstructured—at scale on the cloud.

What is a Data Lakehouse?

A data lakehouse integrates the best capabilities of:

• Data Lakes: Store raw, diverse data types at low cost with flexible schema-on-read access.
• Data Warehouses: Provide ACID transactions, schema enforcement, and fast, reliable analytics typically for structured data.

The lakehouse enables data engineering, BI, and machine learning workflows within one platform without moving or duplicating data.

Key Features

• Unified Storage: Handles raw and curated data on scalable cloud object storage.
• Schema Flexibility: Supports schema-on-read and schema-on-write approaches.
• ACID Transactions: Ensures data integrity and concurrent read/write reliability.
• Support for BI & ML: Optimized for both business intelligence queries and AI/ML workloads.
• Metadata Layer: Provides indexing, governance, and versioning for fast query performance and auditability.

Comparison Table: Data Warehouse vs. Data Lake vs. Data Lakehouse

Aspect	Data Warehouse	Data Lake	Data Lakehouse
Data Types Supported	Structured	Structured, semi-structured, unstructured	Structured, semi-structured, unstructured
Storage Cost	High	Low	Low
Schema Approach	Schema-on-write	Schema-on-read	Flexible (schema-on-read and write)
Transaction Support	ACID compliant	Not ACID compliant	ACID compliant
Performance	High for BI and reporting	Lower for complex queries	High for BI and ML workloads
Use Cases	Business intelligence, reporting	Machine learning, big data exploration	Unified analytics, AI/ML, real-time analytics

Benefits of Data Lakehouse on Cloud

• Cost-effective storage without sacrificing query performance.
• Unifies data engineering, analytics, and AI workflows in one platform.
• Improves data reliability and governance via ACID transactions.
• Supports both batch and streaming data for real-time analytics.
• Simplifies data architecture by reducing silos and duplication.

With its hybrid approach, the Data Lakehouse on Cloud empowers organizations to leverage the flexibility of data lakes and the power of warehouses in a single, scalable architecture – accelerating data-driven innovation for diverse business and AI use cases.

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Happy Exploring!