  As the rate of data collection continues to grow rapidly, developing
visualization tools that scale to immense data sets is a serious and
ever-increasing challenge. Existing approaches generally seek to decouple
storage and visualization systems, performing just-in-time data reduction to
transparently avoid overloading the visualizer. We present a new architecture
in which the visualizer and data store are tightly coupled. Unlike systems that
read raw data from storage, the performance of our system scales linearly with
the size of the final visualization, essentially independent of the size of the
data. Thus, it scales to massive data sets while supporting interactive
performance (sub-100 ms query latency). This enables a new class of
visualization clients that automatically manage data, quickly and transparently
requesting data from the underlying database without requiring the user to
explicitly initiate queries. It lays a groundwork for supporting truly
interactive exploration of big data and opens new directions for research on
scalable information visualization systems.
