Data Lakehouse vs. Data Warehouse: Key Features - PowerPoint PPT Presentation

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Data Lakehouse vs. Data Warehouse: Key Features

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Choosing between a Data Warehouse and a Data Lakehouse depends on your business needs. Data Warehouses are perfect for structured, historical data and support predefined schemas for efficient reporting. On the other hand, Data Lakehouses handle diverse data types, offering flexibility and advanced analytics capabilities. By combining the strengths of both, lakehouses enable cost-effective storage and machine learning. Spiral Mantra helps businesses assess and implement the ideal data architecture to meet their goals. Whether you need a Warehouse or a Lakehouse, our tailored solutions drive success. – PowerPoint PPT presentation

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Date added: 18 December 2024
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Provided by: spiralmantra
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Title: Data Lakehouse vs. Data Warehouse: Key Features


1
Data Lakehouse vs. Data Warehouse
Understand the difference between Data Warehouses
and Data Lakehouses to choose the right solution
for your business needs.
2
What is a Data Warehouse?
  • A Data Warehouse is optimized for structured,
    historical data and analytics
  • Rigid, predefined schema for clean reporting
  • High performance for complex SQL queries
  • Examples Amazon Redshift, Snowflake, Google
    BigQuery

3
What is a Data Lakehouse?
  • The Data Lakehouse combines flexibility with
    performance
  • Supports structured and unstructured data
  • Stores raw and processed data in one platform
  • Ideal for machine learning and advanced analytics
  • Examples Databricks, Delta Lake, Apache Hudi

4
Spiral Mantra Your Data Engineering Partner
  • We specialize in modern data architectures
  • Cloud Migration Strategies
  • Advanced Analytics Consulting
  • End-to-End Data Engineering Solutions

sales_at_spiralmantra.com
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