It was James Dixon, the founder and CTO of Pentaho who coined the term “Data Lake” he explains it as; “If you think of a datamart as a store of bottled water – cleansed and packaged and structured for easy consumption – the data lake is a large body of water in a more natural state. The contents of the data lake stream in from a source to fill the lake and various users of the lake can come to examine, dive in, or take samples.”  Is this just a new trend replacing the Data Warehouse or is it something your company could benefit from? Here are four differences between Data lake and data warehouse to help you…

Differences Between Data Lake And Data Warehouse

1. Format Of Data Stored

Warehouse stores large amounts of structured data. However, a Data Lake can store large volumes of structured, semi-structured or even unstructured data.  When uploading data to a data warehouse you must schema-on-write, model/structure the data.  When you upload the data to a Data Lake you process it in its raw form and then schema-on-read, model it when you are ready to use it.

2. Storage Costs

Data Lake costs have been found to be reduced in comparison to Data Warehouse.  If we take the Hadoop platform as an example, it is an open source software, therefore, licensing and support are free.  In addition, it is designed to be installed on low-cost commodity hardware.

3. Data Security

Because Data Warehouse technology has been around for decades it’s security systems are far more mature than that in the newer Data Lake platforms.  However, this is something of great importance to the Big Data industry, with Data Lake technology fast improving.

4. Users

The Data Warehouse ethos has always been an ‘all are welcome’ and has actively encouraged all in BI and analytics to be users.  However, at this point, a Data Lake has been recommended to be more appropriate for a Data Scientist to gain the most benefit from this solution.  An example of this would be that data within a Data Warehouse is difficult and time-consuming to change, however, it is easier for the user to reconfigure the data within a Data Lake.

Many people ask if there is a difference between a Data Warehouse Solution and a Data Lake Solutions, as you can see there are some significant differences.  This can make it challenging to know which is the most appropriate storage platform for your company’s big data needs.  This is where we can help, with experience in Data Warehouse Consulting and Data Lake Services we can assess your needs and devise the best fit for your project.  To find out more contact us on the link below.

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