SQream Technologies Unveils DB V3.0 GPU-Accelerated Data Warehouse for Massive Data Analytics

SQream Technologies Ltd, developer of SQream DB, GPU-accelerated data warehouse for rapidly analyzing massive data stores at a fraction of the cost, announced the availability of DB v3.0.

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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.

Faster and efficient
DB v3.0 increases big data analytic speeds while allowing organizations to manage their computing resources, permitting database administrators to allocate 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 Ami Gal, co-founder and CEO, SQream. “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, VP, sales and marketing, EMEA, Nvidia Corporation. “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 before.

• Data stores can be ingested and analyzed faster with compressed parquet files

• External table enables direct access to data for fastest available analysis

• 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 implementation

Enriched BI and data science pipeline
SQream DB is more beneficial for data science, as users can quickly load, transform and analyze larger volumes of data faster by using compressed Parquet files. The DB external table syntax adds additional flexibility not found with traditional flat-file bulk loads. With a choice of options for transforming data, loading data via Parquet files is valuable to organizations with variable data sources and schemas. It also includes a version of the optimized Spark connector, which has been specifically optimized for two-way interconnect, leveraging 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. 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
DB v3.0 is offered as a Docker container image, making deployment and upgrades easier with repeatable configuration management and simplified IT installation, while maintaining DB’s query performance and ingest speeds. SQream DB’s adaptive auto-compress feature includes more compression types, designed to handle dynamic and evolving data, while retaining compression ratio and high speed. This version of SQream DB loads data up to 40% faster than before.

Resources:
Schedule a SQream DB trial (registration required).
DB technical WP (registration required).