In today’s fast-paced environment, organizations need near-real time insights to be able to respond to the changing market. But when running complex queries on massive data sets, query latency with traditional systems can span many minutes to hours. SQream reduces latency to seconds or minutes, resulting in always-updated interactive dashboards.
SQream conforms with the ANSI-92 SQL standard, and adds useful capabilities like window functions, regular expressions and more. By converting SQL queries into clever, highly parallelizable relational algebra operations, SQream can rapidly perform complex operations on the massively parallel GPU cores.
SQream supports regular expression pattern matching, letting you effectively filter and sift massive data.
With a single query, SQream can rank the top earners or best-selling products across several time-ranges, calculate moving averages, and more.
SQream rapidly runs complex joins even when data types don’t match – so you can correlate siloed data without normalizing the data series.
A leading telecom operator decided to profile SQream in comparison with its existing MPP data warehouse, consisting of 40 compute nodes in 5 full racks. The test data included several months’ worth of CDRs, coming in at 1.6 TB per week. The server used was a repurposed HP DL380g9 with a powerful NVIDIA Tesla card.