  The promise of ultimate elasticity and operational simplicity of serverless
computing has recently lead to an explosion of research in this area. In the
context of data analytics, the concept sounds appealing, but due to the
limitations of current offerings, there is no consensus yet on whether or not
this approach is technically and economically viable. In this paper, we
identify interactive data analytics on cold data as a use case where serverless
computing excels. We design and implement Lambada, a system following a purely
serverless architecture, in order to illustrate when and how serverless
computing should be employed for data analytics. We propose several system
components that overcome the previously known limitations inherent in the
serverless paradigm as well as additional ones we identify in this work. We can
show that, thanks to careful design, a serverless query processing system can
be at the same time one order of magnitude faster and two orders of magnitude
cheaper compared to commercial Query-as-a-Service systems, the only alternative
with similar operational simplicity.
