  This paper studies the effectiveness of pushing parts of DBMS analytics
queries into the Simple Storage Service (S3) engine of Amazon Web Services
(AWS), using a recently released capability called S3 Select. We show that some
DBMS primitives (filter, projection, aggregation) can always be
cost-effectively moved into S3. Other more complex operations (join, top-K,
group-by) require reimplementation to take advantage of S3 Select and are often
candidates for pushdown. We demonstrate these capabilities through
experimentation using a new DBMS that we developed, PushdownDB. Experimentation
with a collection of queries including TPC-H queries shows that PushdownDB is
on average 30% cheaper and 6.7X faster than a baseline that does not use S3
Select.
