Data Mesh vs. Data Lake: Key Differences and Which to Choose in 2023

Both Data Mesh and Data Lake architectures have their advantages and drawbacks, and selecting the right one for your organization should be a thoroughly considered choice. A Data Mesh is a novel data platform design paradigm that emphasizes domain-driven decentralized data management, self-serve data infrastructure, and a federated governance model. On the other hand, a Data Lake is a centralized repository for storing raw data that can be processed and analyzed for different business purposes. The primary difference between these two architectures lies in their design principles: Data Mesh emphasizes a decentralized approach to data management, while Data Lake takes a centralized approach. Factors such as the complexity of data models, existing data infrastructure, transformation needs, and data observability must be taken into consideration when deciding between the two approaches.