Seamless, Rapid Integration with Hadoop and Legacy Data Warehouses Propels Analytics and AI/ML Capabilities, Removing Data Size Barriers while Reducing Query Time by up to 80%
TEL AVIV, ISRAEL, January 22, 2020 – SQream announced today the latest release of its flagship data analytics engine, SQream DB v2020.1. SQream DB v2020.1 is the first release of 2020, with a strong focus on rapid integration into existing Hadoop and legacy data warehouse ecosystems. SQream DB enables the analysis of significantly more data and dimensions, at the fastest query times possible for massive data volumes, revealing previously unobtainable critical business insights and decision-making capabilities.
SQream DB v2020.1 is designed for enterprises with massive data stores, who are not able to analyze enough of their data to deliver new and critical insights to propel their business and drive competitive advantage. Analytics that were previously too long-running, or were simply not achievable in the existing ecosystem, are now achievable with SQream DB.
“Enterprises are facing huge challenges in analyzing the exponentially growing data they have stored in Hadoop and legacy data warehouses. They can’t analyze the amount of data they want to, the analytics are taking way too long to be effective, or they need to improve the efficiency of their AI/ML data pipeline,” said Ami Gal, CEO, and co-founder of SQream. “With SQream DB v2020.1, companies can rapidly deploy SQream DB into their existing data ecosystem to analyze much more data, much more quickly, providing data scientists and business stakeholders with significantly improved data insights.”
A review of SQream DB v2020.1 was presented in a webinar on January 29. Watch the on-demand webinar:
SQream DB v2020.1 highlights and enhancements include:
- Streamlined HDFS Integration – Native HDFS support dramatically improves data offloading and ingest when deployed alongside Hadoop data lakes. Together with new ORC support, SQream DB can now not only read, but also write data and intermediate results back to HDFS for other data consumers, to significantly improve analytics capabilities from a Hadoop data pipeline.
- ORC Columnar Format Joins Parquet – In conjunction with External Table and optimized HDFS functionality, ORC can now be used to interface directly with tables created with Hadoop HIVE and Impala, without ETL or conversion. This capability simplifies production deployments for customers with enterprise Hadoop data lakes.
- S3 Connectivity – Customers with columnar data residing on S3 data lakes can use SQream DB v2020.1 to access the data directly. All that is needed is to simply point an external table to an S3 bucket with Parquet, ORC, or CSV objects. This feature is available regardless of where SQream DB is installed.
- Direct Queries of Massive Data – Bundled in the latest version is the new DB-API compliant Python driver, which can be used in conjunction with Pandas, Numpy, and AI/ML frameworks like TensorFlow for direct queries of huge datasets.
- Faster Iteration of AI/ML Workflows – Explore data, and run predictions and calculations with advanced window and statistical functions support. Make AI /ML data exploration iterations faster, easier, and more efficient, feeding data into machine learning models in Python, R, or any other framework.
- More Powerful Analytics – Enhanced window functions improve the execution of the most complex analysis and reporting tasks. Also included are new frames and frames exclusion, which add complex analytics capabilities to the already powerful and popular window function concept.
SQream DB v2020.1 is specifically designed for handling very large analytic workloads, and enabling the rapid resolution of data challenges faced by enterprises with Hadoop or legacy data warehouses. SQream DB greatly accelerates analytics, turning exponentially growing data stores into a competitive differentiator. Enterprises improve performance levels while achieving business critical insights, faster.
SQream develops and markets SQream DB, designed to obtain unparalleled analytic insights from massive data stores. Global enterprises and solution vendors use SQream DB to analyze more data than ever before, while achieving improved performance, reduced footprint, significant cost savings and the ability to scale the amount of data they analyze to hundreds of terabytes and more. SQream DB is available both on premise and in the cloud. To learn more, visit sqream.com or follow us on twitter @sqreamtech.