Data Warehousing
  • Data Warehousing
  • Readme
  • Fundamentals
    • Terms to Know
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    • Application Tiers
    • Operational Database
    • What is a Data Warehouse
      • Typical Data Architecture
      • Problem Statement
      • Features of Data Warehouse
      • Need for Data Warehouse
      • Current State of the Art
    • Activities of Data Science
    • Types of Data
    • Data Storage Systems
    • Data Warehouse 1980 - Current
    • Data Warehouse vs Data Mart
    • Data Warehouse Architecture
      • Top-Down Approach
      • Bottom-Up Approach
    • Data Warehouse Characteristic
      • Subject Oriented
      • Integrated
      • Time Variant
      • Non Volatile
    • Tools
    • Cloud vs On-Premise
    • Steps to design a Data Warehouse
      • Gather Requirements
      • Environment
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      • Choosing ETL / ELT Solution
      • Online Analytic Processing
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    • Dataset Examples
    • Thoughts on some data
  • RDBMS
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    • Online vs Batch
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    • Connect to Elvis
    • SQL Concepts
      • Basic Select - 1
      • Basic Select - 2
      • UNION Operators
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      • Sub Queries
      • Derived Tables
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    • Practice using SQLBolt
  • Cloud
    • Overview
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    • AWS
      • AWS Global Infrastructure
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    • Storage Formats
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    • Medallion Architecture
    • Delta
  • Data Warehousing Concepts
    • Dimensional Modelling
      • Star Schema
      • Galaxy Schema
      • Snowflake Schema
      • Starflake Schema
      • Star vs Snowflake
      • GRAIN
      • Multi-Fact Star Schema
      • Vertabelo Tool
    • Dimension - Fact
    • Sample Excercise
    • Keys
      • Why Surrogate Keys are Important
    • More Examples
    • Master Data Management
    • Steps of Dimensional Modeling
    • Types of Dimensions
      • Date Dimension Table
      • Degenerate Dimension
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      • Static Dimension
      • Conformed Dimensions
      • Slowly Changing Dimensions
        • SCD - Type 0
        • SCD - Type 1
        • SCD - Type 2
        • SCD - Type 3
        • SCD - Type 4
        • SCD - Type 6
        • SCD - Type 5 - Fun Fact
      • Role Playing Dimension
      • Conformed vs Role Playing
      • Shrunken Dimension
      • Swappable Dimension
      • Step Dimension
    • Types of Facts
      • Factless Fact Table
      • Transaction Fact
      • Periodic Fact
      • Accumulating Snapshot Fact Table
      • Transaction vs Periodic vs Accumulating
      • Additive, Semi-Additive, Non-Additive
      • Periodic Snapshot vs Additive
      • Conformed Fact
    • Sample Data Architecture Diagram
    • Data Pipeline Models
    • New DW Concepts
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  1. Fundamentals

Cloud vs On-Premise

PreviousToolsNextSteps to design a Data Warehouse

Last updated 2 years ago

Feature
Cloud Datawarehouse
On-Premise

Scalability

Instant Up / Down, Scale In / Out

Reconfiguring / purchasing hardware, software, etc.

Availability

Up to 99.99%

Depends on infrastructure.

Security

Provided by cloud provider

Depends on the competence of the in-house IT team.

Performance

Serve multiple geo locations, helps query performance

Scalability challenge

Cost-effectiveness

No hardware / initial cost. Pay only for usage. *If not managed carefully, it could cost a fortune.

Requires significant initial investment, salary.

src:

https://www.scnsoft.com/analytics/data-warehouse/cloud