Solution architects are often faced with the task of designing an architecture for a system or for re-architecting an existing system. This involves deciding the right components that go into the software architecture along with technologies used to instantiate the architecture stack. With a continuously evolving technology landscape, the choices of technology and the corresponding combinations leading to architecture-based technology-stacks can increase exponentially. With the number of technologies growing manifold, this task becomes non-trivial and is purely reliant on the domain expertise of the solution architect. We propose and build the Architecture-based Technology Advisor (ATA), which addresses these issues by providing a meaningful subset of ranked architecture-based technology stacks as recommendations to users. Most of the efforts till date provide recommendations of a particular technology in isolation, which corresponds to a single component (or a subset) of the overall software architecture. ATA relies on a rule repository of technologies, populated using a functional feature set. We propose a recommendation algorithm, that constructs a generic weighted acyclic dependency graph, which facilitates the pruning of a wide variety of technology options available based on the requirement. ATA algorithm uses a similarity metric, derived from domain knowledge and industry best practices, to determine the closest match to a particular user requirement. ATA also determines the interoperability of technologies that have been recommended as a part of the software architecture stack. The ATA algorithm gathers feedback for recommendations and uses this historical data to improve future recommendations. We illustrate through experiments, the utility and capabilities of the Architecture-based Technology Advisor.