The Silicon Review
When it comes to modern big data systems and related cloud computing platforms, you’d think that storage capacity, processing power and network bandwidth would be the primary elements of an efficient system. It’s becoming increasingly clear, however, that’s not the case, especially as more businesses emphasize data acceleration. Data acceleration essentially refers to the rate or speed at which large troves of data can be ingested, analysed, processed, organized and converted to actionable insights. By focusing on data acceleration as a whole, platform developers and network engineers can deliver targeted solutions to improve power, performance and efficiency of these platforms.
SQream is one such data acceleration platform empowering organizations to analyze the full scope of their massive data – from terabytes to petabytes – enabling them to achieve previously unattainable critical insights. Global enterprises integrate SQream into their existing data pipeline to analyze more data than ever, for improved performance, reduced footprint, and cost-efficient scaling of the amount of data being analyzed.
Revolutionary Data Acceleration Products and Services Provided
SQream Data Acceleration Platform: Massive data doesn’t have to mean settling for partial analytics and missing out on critical insights. The SQream data acceleration platform is a database management system specifically designed to handle massive data sets – from dozens of terabytes to petabytes. SQream shines where others fail – bringing complex queries that take days down to hours, and hours, down to minutes. SQream conquers the largest workloads by combining available CPU, GPU, RAM, and storage resources – enabling reports, interactive dashboards, and ad-hoc queries. This balance of CPU and GPU operations ensures optimal performance. The result is faster response times, even on the most complex interactive dashboards.
SQL GPU Database: SQream was built to harness the raw brute-force power and high throughput capabilities of the GPU, on-premise, on the cloud or hybrid. With MPP-on-chip capabilities, the fully relational SQream DB SQL database comes with automatic tuning, ultra-fast performance, class-leading compression, and extreme scalability. SQream easily ingests and analyzes an organization’s largest datasets. Combining the throughput-oriented GPU with some best-of-breed data techniques, SQream DB scales from terabytes to petabytes with ease. Together with the formidable JOIN, which SQream DB runs entirely and effectively in-GPU from its inception, GPU-acceleration is the backbone of SQream’s massive data analytics capabilities.
SQL Query Acceleration: 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 to 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.
Columnar SQL Database: The onslaught of the Massive Data Era is felt by solution providers who have big data analytics modules built into their offerings. Performance decreases and other functionality come to a halt as complex queries run with multi-dimensional analytics. Trying to resolve these issues with remote service is problematic at best when even possible. It is imperative that the database for solutions with heavy analytics crunching provide a reliable small footprint, yet full-featured HPC system, to ensure maximum analytics performance even as the solution data grows. SQream scales to virtually unlimited data sizes. Grow from to terabytes to petabytes without having to expand expensive legacy systems.
The Leader Upfront
Ami Gal, co-founder, serves as the Chief Executive Officer of SQream. He and brings more than 20 years of technology industry expertise and executive management experience to his role with the company. Prior to SQream, Mr. Gal was Vice President of Business Development at Magic Software where he generated new growth engines around high performance and complex data integration environments. Previously, he co-founded Manov, later acquired by Magic Software, and played an integral role in the company’s secondary offering.
Over the last decade, Ami has invested in and served on the boards of several startups, as well as mentored founders in startup programs including IBM Smartcamp, Seedcamp and KamaTech.