Combining the best of both worlds
Imagine a warehouse stocked with well-organised components in neat rows and stacks. Now, think of a lake, full to the brim with water, fish and other objects all jumbled together with no immediate order imposed on them. It’s relatively straightforward to find and access a specific object located in a warehouse – while it requires different processes to identify and extract specific content from a lake.
Like their namesakes, data warehouses and data lakes differ quite profoundly in how they store and process what fills them: information.
A data warehouse deals best with moderate amounts of structured data, which is used mainly in reporting and service delivery.
A data lake is best at handling large amounts of raw and unstructured data, which is used mainly in data science, machine-learning exploration, and similar applications.
Do we need really need to make a choice between data lake or data warehouse?
The main problem with this either/or approach? Today’s companies need to be able to handle all types data, and use them in all types of scenarios. In other words, having to choose between a data lake or warehouse is almost always a case of choosing the lesser evil. This is why many organisations now use both in tandem, leading to higher levels of complexity and duplicated data.
Enter the data lakehouse
Enter the data lakehouse: an open architecture that combines the best features of – you guessed it – data lakes and data warehouses, with increased efficiency and flexibility as a result. Made possible by the rising trend of open and standardised system design, data lakehouses can apply the structured approach of a warehouse to the wealth of data contained in a data lake.
The main features of a data lakehouse
- Handle various data types: structured, unstructured and semi-structured
- Enjoy simplified data governance and enforce data quality across the board
- Get business intelligent support directly on the source data, which means that BI users and data scientists work from the same repository
- Get support for data science, machine learning, Structured Query Language (SQL), and analytics – all in one place