Data Warehouse vs Data Lake- Five Key Differences You Must Know

Know The Five Key Differences Of Data Lake vs Data Warehouse- You Must Be Aware Of


‘Big data' is relatively a new term but it has gained amazing popularity among data and analytics practitioners. In the last several years, big data has gained a lot of popularity as it has opened a new way of data storing and maintaining with a stunning level of security. When it comes to big data, two related terms also take places such as data warehouse and data lake. These terms are a bit confusing to many people as they cannot differentiate one from another. There are a lot of data lake consulting services available out there. But which data service you actually need that you can easily understand when you can successfully differentiate these two things.  

What is Data Warehouse?  

The data warehouse is a great blend of superior technologies and components that ensure the strategic use of data. It is able to collect as well as manage data from various varied sources and turn them into meaningful business insights. It is actually an effective way to store a large amount of information. Generally, such type of data gets used for query and analysis. You will not see the use of such data in the area of transaction processing. It will be fair if we say that it is a fair process to turn data into useful information.  

What is Data Lake?  

A data lake is nothing but a great storage repository. It is able to store a large amount of properly structure, unstructured, and semi-structured data. Any type of data can be stored here without changing its native form and there is no worry about the data storage limits or file type. We can see the use of Data Lake when someone wants to perform analytical performance along with native integration tasks.  

Data Lake is actually like a large data container with great storage capacity and that’s why it is named in such a way. You know that in a lake you can see multiple tributaries taking place in the same way in a Data Lake we can see various types of data with different sizes.  

Key differences: Data Warehouse vs. Data Lake 

1.      Data Lake is able to store all types of data irrespective of the source and structure type of the data. But data warehouse is able to store data with quantitative metrics along with their attributes.  

2.      Data Lake is a proper data storage repository that is able to store all types of data and there is no limit on data quantity. On the other hand, Data Warehouse is a fine blending of superior technologies that only ensures the proper and strategic use of data.  

3.      Data Lake is able to define the schema when the data storing will be completed. Data Warehouse is able to identify the schema even before the data storing process starts.  

4.      Data Warehouse uses Extract Transform Load (ETL) process. But Data Lake uses the ELT process i.e. Extract Load Transform.  

5.      If you are someone who has the requirements of in-depth data analysis, we will suggest you to going for Data Lake. But if you have the requirements of operational usages of data, it will be better if you go for Data Warehouse.  

These are the key differences between Data Lake and Data Warehouse. Before choosing any of these, you should start by analysing your requirements. Once you know about your requirements, you will be able to select the best thing for you. If you still cannot decide which one will be the best for you, you can take professional consultation services to be completely risk-free.