Company Profile 

SQream Technologies delivers the most flexible database for huge dataset analytics. Global enterprises use SQream DB to analyze more data than ever before. SQream DB delivers business intelligence acceleration for smart, informed, near real-time time decision making based on large data sets, in the age of immense amounts of data.

SQream Technologies has the knowledge and experience to implement GPU-powered SQL analytics projects across all domains and departments, while simplifying existing architectures.

Solution at a Glance

SQream DB is the GPU Big Data database for huge data sets.
Built from scratch, SQream DB harnesses the unique performance of graphical processors (GPUs) for handling hundreds of terabytes, trillions of rows – in a small hardware footprint.

SQream DB gives fast insights on very large data sets, especially with large, complex, multi-table join queries. Join huge fact tables with ease, without worrying about primary keys and pre-indexing.

SQream DB is a no-hassle SQL big-data solution, that integrates easily with your existing BI environment. SQream DB lets you focus on your data, not on the infrastructure.

Our Offering

SQream DB has been adopted by several telecoms, enhancing the way they perform big data analytics. Our customers query trillions of rows of data faster than ever before, uncovering hidden insights in data. SQream DB helps telecoms correlate different sources including CDRs, network events, billing, marketing, and more – for a holistic customer-centric approach.

Customer Challenges and Benefits

Anyone facing challenges with getting insights from their huge data sets, or correlating data from different silos, like marketing, billing, network, and IoT sensors will love SQream DB’s GPU technology.

With super-fast ingest and a flexible columnar SQL engine anyone can interact and correlate data, and gain valuable insights in minutes.

Unique Selling Points and Differentiators

  • 100X faster insights than other leading DBMSs
  • Massive scalability – analysis of petabyte-scale datasets
  • 100 terabytes in a standard 2U server and a handful of GPU card
  • 80% more cost-effective than the average cost of big data analytics database
  • Simplicity in use – Standard SQL (no special skills required, no indexing, no cubes)
  • Fits in with existing BI infrastructure – industry standard connectors (ODBC, JDBC, .Net etc.)
  • On the fly compression and decompression for lower storage costs
  • Operating ease
  • Lowest overall TCO