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What are differences between schema on read vs schema on write

Hello friends, If you are talking about data, database , data-warehouse or big data nothing will complete without schema. Schema plays an important role in Data Platform. Today I am exploring about Schema on write and schema on read in respect of datawarehouse and data lake. Let see differences.

 Schema on write 
  • Structured Data, 
  • RDBMS, 
  • OLAP / Data-warehouse. 
  • Heavy ETL (extract-transform-load) role in data movement. 
  • Change in data-model is costly. 
  • work well in range of Data Mart.
  • User have set of questions.
  • Business Analysis.
  • Collect  Data - Apply Schema - Write Data - Analyze.


Schema on read 

  • Structure & Un-structured Data. 
  • RDBMS, NoSQ & Hadoop. 
  • BigData / Data Lake.
  • ELT (extract-load-transform) & Low cost extraction.
  • Schema is just a structured file can be switched dynamically.
  • Ideal for large volume of data.
  • User is exploring data without pre-defined query.
  • Data science & Research.
  • Collect Data - Write Data - Apply Schema- Analyze.


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Comments

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