Data Ingestion Architectures

Data ingestion is the process of collecting, transferring, and loading data from various sources to a destination where it can be stored and analyzed. Several data ingestion architectures can be used to collect data from different sources and load it into a data warehouse, data lake, or other storage systems. These architectures can be broadly classified into two categories: batch processing and real-time processing. How you choose to ingest data will depend on the volume, velocity, and variety of data you are working with, as well as the latency requirements of your use case.

Lambda and Kappa architectures are two popular data ingestion architectures that combine batch and real-time processing to handle large volumes of data efficiently.