Augment DWH and DBMS Capabilities

Organizations rely on legacy databases and data warehouses to accommodate big data analytics. But as analytics grow from big to massive, these systems often become overloaded. Users are left waiting inordinate amounts of time for their queries to complete – if they can be completed at all. SQream integrates into your data pipeline to bridge the gap between your legacy system’s capabilities and the scale and performance requirements of the Massive Data Era.

Enable Previously Infeasible Analytics
SQream completes complex queries that other systems cannot, thanks to its GPU-accelerated processing and non-reliance on RAM.
Shorten Extremely Long-Running Queries
Offloading data-heavy queries to SQream DB significantly accelerates their processing, from days to hours, and hours to minutes or even seconds.
Achieve Cost-efficient Scalability
By decoupling compute resources from storage, SQream cost-efficiently scales to virtually unlimited data sizes, significantly reducing your TCO.
How Three Companies Reduced TCO up to 60% for their Data Warehouse Appliance
This webinar highlights how three companies significantly improve data access, data management, and query performance, while greatly reducing the TCO of their DWH appliance.
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AIS Improves Customer Service and Network Operations
Learn how AIS improved customer services and network operations by implementing SQream alongside their Greenplum system.
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ACL Achieves Deep Analytics and Reporting
Discover how SQream was deployed alongside ACL’s relational database to improve their customer experience with deep data analytics, richer reports, and a self-service solution.
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SQream DB for SAP Hana
Learn how integrates with SAP Hana to cost-effectively scale from big data to massive data, while enabling complex analytics that were previously infeasible.
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