Data Lake vs Data Warehouse: The Era of Big Data!

Source: educba.com

 

“Every Company has big data in its future, and every company will eventually be in the data business” – Thomas H Davenport.

 

As we know that data is an essential part of the business process for any company, making it an asset for them. The large quantity of structured and unstructured that are collected by organizations must be stored somewhere before it can be process for analysing. There comes Data Lake and Data Warehouse as a popular solution for storing these big data. The aim of this blog is to discuss the difference between the two to help you make aware on how to manage your precious large data. Let us first see, what is Data Lake and Data Warehouse?

Data lake:

A data Lake is a system of stored in its natural format, usually object blobs or files. A data lake can include structured data from relational databases, semi structured data, unstructured data, and binary data. A data lake can be established “on premises” or “in the Cloud”. – according to Wikipedia.

Data Warehouse:

Data Warehouses are central repositories of Integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise. – according to Wikipedia.

Key difference between Data Lake and Data Warehouse:

1.State of the Data:

A Data Warehouse stores changed and curated data while the Data Lake store any old data regardless of its state.

2.Storage Cost:

Storing Data in Data Warehouse is costlier and time-consuming as compare of Data Lake which is inexpensive.

3.Processing Time:

Data Lake allows its users to get to their results more quickly compare to Data Warehouse which requires more time.

4.Storage Capabilities:

Data Lake is designed to have greater capacity for data as compared to Data Warehouse.

5.Agility:

In Data Warehouse databases are less agile to configure as they are structured by source while in Data Lake have more agility which makes it easy to configure and reconfigure the applications.

6.Security:

Data Warehouses are much more secure than the Data Lakes.

7.Users:

Data Warehouses are used mostly by the business professionals while Data Lakes are mostly used in scientific fields.

8.Performance:

Data processing speed is good in Data Warehouse as they have small datasets while Data Lake have large datasets resulting in low processing speed.

Which approach to choose?

Technologies in both sides continues to gradually develop but does your business needs a Data Warehouse or Data Lake? The answer depends upon which best fits your case and your company’s needs. Sometimes we need a combination of both storage option.

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