SQream and Hitachi Vantara Announce Partnership
TEL AVIV, Israel, Sept. 6, 2022 -- SQream, the developer of a hybrid platform for rapid data analytics at scale, and Hitachi Vantara, a leader in the field of data management and digital infrastructure solutions, are collaborating to offer solutions that will enable large organizations to better utilize analytic systems like Hadoop-Hive, Cloudera and Teradata to accelerate critical insights and run AI/ML models over even the largest data using SQream's data acceleration platform and Hitachi Vantara's innovative object storage offerings.
SQream, a Hitachi Vantara Create partner since 2021, offers the solutions in cooperation with Hitachi Vantara to address the challenge of growing data within the enterprise, and the difficulty organizations face in analyzing the full scope of this data to achieve accurate business insights when they need them most. SQream's Data Acceleration Platform integrates with Hitachi Content Software for File, a highly parallel NVMe-based file system and Hitachi Content Platform (HCP) object storage, to deliver targeted performance and attractive economics.
The companies recently launched a joint project helping a major global manufacturer enable anomaly detection via artificial intelligence and high-performance computing machine learning applications. Using Hitachi Vantara storage systems and SQream for rapid analytics, the manufacturer was able to ingest and continually analyze a multi peta-scale database composed of manufacturing machine sensor events, ingested to thousands of tables. This led to a significant improvement in Overall Equipment Efficiency.
"Extensive data analysis has become synonymous with long ETL processes and queries that, in turn, result in many organizations receiving valuable insights too late and less accurate AI/ML models," said Benny Yehezkel, CRO of SQream. "This joint offering with our partner Hitachi Vantara accelerates Total Time to Insights (TTTI) and turns data into business value with unprecedented cost-effectiveness, providing great potential for our common customers."
"There is no question that customers are seeking ways to achieve faster insights for time-sensitive and strategic use cases," says Tanya Loughlin, director of product marketing, Content Platforms for Hitachi Vantara. "Together with SQream, we are excited to empower our customers to be even more data-driven, generating new value from their data for faster insights and better decision making."
Earlier this year, HCP was recognized as a leader in GigaOm's 2022 Radar Report for Unstructured Data, as well as a DCIG Top 5 On-Premises SDS Object Storage Solution because of its compelling outcomes, strengths of Hitachi Content Intelligence, and comprehensive data management strategy for IoT, big data, and unstructured data.
Hitachi Content Platform offers customers comprehensive, intelligent data management solutions beyond object storage, providing innovative unstructured data management solutions to help technology leaders cost effectively safeguard their data while realizing its full potential. For more information, please click here.
About SQream
SQream makes it makes it possible to ask bigger questions of extremely large, complicated data sets. With no off-limits questions, data scientists in manufacturing, telecom, and finance get unprecedented new insights at exceptional speed. For far too long, decision makers have known that the critical answers they needed were in their data, but it was impossible to get to them. With SQream, you can finally "dig deeper, go faster, and reach anywhere" so you're able to ask bigger questions of your data – on prem, in the cloud, or at the edge.
About Hitachi Vantara
Hitachi Vantara, a wholly-owned subsidiary of Hitachi Ltd., delivers the intelligent data platforms, infrastructure systems, and digital expertise that supports more than 80% of the Fortune 100. To learn how Hitachi Vantara turns businesses from data-rich to data-driven through agile digital processes, products, and experiences, visit www.hitachivantara.com.
Source: SQream
