Introducing SQream DB v3.0: The Most Advanced GPU-Accelerated Data Warehouse for Massive Data Analytics

New release introduces numerous innovative features for rapidly ingesting and analyzing massive amounts of data for previously unattainable analytics

TEL AVIV, ISRAEL — (September 5, 2018) – SQream, developer of SQream DB, the leading GPU-accelerated data warehouse for rapidly analyzing massive data stores at a fraction of the cost, announced today the general availability of SQream DB v3.0. The new version enables enterprises to quickly and easily load massive volumes of data in the range of terabytes to petabytes for analysis, while generating higher quality business intelligence faster than any other data store at these volumes.

Get hands-on: schedule a SQream DB trial →
Learn more in our SQream DB technical white paper →
Why SQream DB?→

Faster and More Efficient

SQream DB v3.0 increases big data analytic speeds while allowing organizations to efficiently manage their computing resources, permitting database administrators to allocate the highest quality-of-service to those who need it most.
Available to use on-premise or in the cloud, SQream DB can achieve almost twice as fast load times and up to 15x faster queries for multi-table joins and count distinct operations compared to previous versions of SQream.
“SQream DB v3.0 is an exciting new development in integrating NVIDIA GPU analytics to quickly and efficiently generate business intelligence,” said SQream co-founder and CEO Ami Gal. “It provides added flexibility and performance to ingest and process huge amounts of data and deliver near real-time analytical queries so enterprises can gain insights at greater speeds. Enterprises are able to more efficiently use existing infrastructure while decreasing cost of ownership and increasing ROI.”
“Businesses are led by data analytics and business intelligence but need to accelerate their interaction with the data to make it viable,” said Jaap Zuiderveld, vice president of Sales and Marketing for EMEA at NVIDIA. “SQream’s ability to provide accelerated analytics on massive data stores by using NVIDIA Tesla Tensor Core V100 GPUs is already making a real change in industries such as telecom, retail, and finance.”

SQream DB’s recent innovations are designed to modernize data infrastructure, by opening up access to more data than ever before.

• Data stores can be ingested and analyzed faster with compressed Parquet files
• External Table enables direct access to data for fastest available analysis
• Highly optimized Spark connector enables faster integration into data science pipelines
• Dynamic Workload Management provides on-the-fly resource workflow prioritization
• Reduced complexity with built-in auto-compress and class-leading SQL query optimizer
• Easy to deploy Docker container images makes for rapid and efficient implementation

Enriched BI and Data Science Pipeline

SQream DB is now even more beneficial for data science, as users can quickly load, transform and analyze larger volumes of data faster by using compressed Parquet files. The new SQream DB External Table syntax adds additional flexibility not found with traditional flat-file bulk loads. With a broad choice of options for transforming data, loading data via Parquet files is extremely valuable to organizations with variable data sources and schemas. SQream DB also includes a new version of the highly optimized Spark connector, which has been specifically optimized for two-way interconnect, leveraging SQream DB’s fast native communication protocol.

Advanced Workflow Management and Prioritization

Modern enterprises have many users with variable workloads and different usage demands for each department. With the ever-growing size of data stores, organizations have to effectively manage their resources to generate business insights to stay ahead of the competition. SQream DB v3.0 comes equipped with Dynamic Workload Management, which allows organizations to ensure they effectively manage compute resources by allowing on-the-fly changes to resource allocation. Projects can be prioritized in order of urgency and importance rather than on a first-come, first-served basis.

Rapid Implementation and Data Ingest

SQream DB v3.0 is now also offered as a Docker container image, making deployment and upgrades much easier with repeatable configuration management and simplified IT installation, while maintaining SQream DB’s superior query performance and ingest speeds. SQream DB’s adaptive auto-compress feature now includes more compression types than ever, designed to handle dynamic and evolving data, while retaining excellent compression ratio and high speed. This version of SQream DB loads data up to 40% faster than before.

Get hands-on: schedule a SQream DB trial →
Learn more in our SQream DB technical white paper →
Why SQream DB?→

About SQream

SQream develops and markets SQream DB, a GPU data warehouse designed to enable unparalleled business intelligence from massive data stores. Global enterprises use SQream DB to analyze more data than ever before, while achieving improved performance, reduced footprint, significant cost savings and the ability to scale the amount of data they analyze to hundreds of terabytes and more. SQream DB is available both on premise and in the cloud. To learn more, visit sqream.com or follow us on Twitter @sqreamtech
Media Contacts:
Josh Turner
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+972-54-949-6526
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David Leichner
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