SQream releases DB v3.0, its advanced GPU-accelerated data warehouse for massive data analytics



SQream, developer of SQream DB, a 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. This version enables enterprises to 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.

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.

SQream DB v3.0 increases big data analytic speeds while allowing organizations to 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, reduces complexity with built-in auto-compress and class-leading SQL query optimizer, and easy to deploy Docker container images makes for rapid and efficient implementation.

Modern enterprises have many users with variable workloads and different usage demands for each department. With the growing size of data stores, organizations have to 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.

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 percent faster than before.

 

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