Difference between Database vs Data lake vs Warehouse

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Difference between Database vs Data lake vs Warehouse

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Database
=========
Transactional data
OLTP (online transaction processing)
Structured data
Recent data - day to day data.
Example - online banking transaction.
Oracle, Mysql
Schema on Write

DatawareHouse - DWH
====================

Analytical processing where we require a lot of historical data to find the insights.

The moment we run complex queries on our database with an intent to do some analysis then your day to day transaction will become slow.

we take the data from databases and migrate it to Datawarehouse to do analytical processing.

we get the data from multiple sources.

Structured Data - Schema on write.

example - TeraData

storage cost is high but lesser than your database.

ETL process -

suppose your data is in database

extract the data

Transform it (is a complex process)

Load it to Datawarehouse

This approach reduces our flexibility.
Data Lake
==========
to get insights from huge amount of data.

the data is present in its raw form. It can be structured or unstructured.

Log File - we can directly have this file in raw form in data lake.

ELT process - Extract Load & Transform.

HDFS, Amazon S3

Cost effective..

Schema on Read.

create structure to visualize or see the data.

it gives you enough flexibility.

#bigdata #dataengineering

Видео Difference between Database vs Data lake vs Warehouse канала Sumit Mittal