  In the age of big data, more and more applications need to query and analyse
large volumes of continuously updated data in real-time. In response,
cloud-scale storage systems can extend their interface that allows fast lookups
on the primary key with the ability to retrieve data based on non-primary
attributes. However, the need to ingest content rapidly and make it searchable
immediately while supporting low-latency, high-throughput query evaluation, as
well as the geo-distributed nature and weak consistency guarantees of modern
storage systems pose several challenges to the implementation of indexing and
search systems. We present our early-stage work on the design and
implementation of an indexing and query processing system that enables realtime
queries on secondary attributes of data stored in geo-distributed, weakly
consistent storage systems.
