Data architecture describes the structure of an organization's logical and physical data assets and data management resources, according to The Open Group Architecture Framework (TOGAF).
A data mesh is an architectural paradigm that connects data from distributed sources, locations, and organizations, making data from multiple data silos highly available, secure and interoperable by abstracting away the complexities of connecting, managing and supporting access to data.
Lambda architecture is a data-processing architecture designed to handle massive quantities of data by taking advantage of both batch and stream-processing methods. This approach to architecture attempts to balance latency, throughput, and fault-tolerance by using batch processing to provide comprehensive and accurate views of batch data, while simultaneously using real-time stream processing to provide views of online data.
Kappa architecture is a simplification of Lambda architecture. It is a data processing architecture designed to handle stream-based processing methods where incoming data is streamed through a real-time layer and the results of which are placed in the serving layer for queries.