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SQream Delivers Enhanced Data Warehouse Solution


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SQream is releasing an upgraded version of its GPU-accelerated data warehouse for rapidly analyzing massive data stores.

SQream DB v3.0 enables enterprises to quickly and easily load massive volumes of data in the range of terabytes to petabytes for analysis.

“When you talk about performance there are quite a few things you need to address: it’s not only about the performance of the queries, it’s also about how fast and easy it is to put data in the database,” said Ami Gal, CEO of SQream.

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, according to the company.

New innovations and features include:

  • 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

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.

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.

Additionally 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.

Plans for the future include automatic query optimization, more collaborations with storage vendors, and more, Gal explained.

“This is a very long list of enhancements but the main message is that we integrated SQream DB into many types of sources of data so it’s much easier to use the product, much easier to integrate, it’s becoming seamless, and it’s becoming part of running the data pipeline,” said Gal. “This is something we’re pretty proud of.”

For more information about these updates, visit sqream.com.


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