Posts Tagged ‘NoSQL’

How Schema On Read vs. Schema On Write Started It All

Thomas Henson

Thomas Henson

Unstructured Data Engineer and Hadoop Black Belt at Dell EMC
Thomas Henson is a blogger, author, and podcaster in the Big Data Analytics Community. He is an Unstructured Data Engineer and Hadoop Black Belt at Dell EMC. Previously he worked helping Federal sector customers build their first Hadoop clusters. Thomas has been involved in the Hadoop Community since the early Hadoop 1.0 days. Connect with him @henson_tm.
Thomas Henson
Thomas Henson

Article originally appeared as Schema On Read vs. Schema On Write Explained.

Schema On Read vs. Schema On Write

What’s the difference between Schema on read vs. Schema on write?

How did Schema on read shift the way data is stored?

Since the inception of Relational Databases in the 70’s, schema on write has be the defacto procedure for storing data to be analyzed. However recently there has been a shift to use a schema on read approach, which has led to the exploding popularity of Big Data platforms and NoSQL databases. In this post let’s take a deep dive into what are the differences between schema on read vs. schema on write.

What is Schema On Write

Schema on write is defined as creating a schema for data before writing into the database. If you have done any kind of development with a database you understand the structured nature of Relational Database(RDBMS) because you have used Structured Query Language (SQL) to read data from the database.

One of the most time consuming task in a RDBMS  is doing Extract Transform Load (ETL) work. Remember just because the data is structured doesn’t mean it starts out that way. Most of the data that exist is in an unstructured fashion. Not only do you have to define the schema for the data but you must also structure it based on that schema.

For example (more…)

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