Practical Lakehouse Architecture

Chapter 2. Traditional Architectures and Modern Data Platforms

In Chapter 1, we discussed lakehouse architecture—a new approach for implementing data platforms. To truly appreciate any new technology, you first need to understand the capabilities and limitations of its previous generations. Thus, to appreciate the value of lakehouse architecture, it’s essential to understand the current and previous generations of data architectures. We will discuss these previous generations, also known as the “traditional architectures” in detail in this chapter.

We’ll first discuss how the traditional architectures like data warehouses and data lakes are implemented using the on-premises infrastructure. I’ll walk you through the key characteristics, benefits, and limitations of data platforms built using these architectures.

Next, we’ll explore the modern data platforms built using cloud technologies and what today’s data-driven organizations expect from them. Organizations implement their modern data platforms using either a standalone or combined approach:

The standalone approach

Comprises a system built using a data warehouse or a data lake

The combined approach

Uses both the data warehouse and the data lake, making it a two-tier architecture

As seen in Chapter 1, lakehouse architecture also helps build modern data platforms and is gaining industry attention. In the last section of this chapter, we’ll compare the standalone and combined approaches with the lakehouse architecture to ...