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Vertica Launches Version 11: Major Features & Upgrades Introduced

Vertica Launches Version 11: Major Features & Upgrades Introduced

  • Vertica 11 includes more in-database machine learning capabilities with the latest release of VerticaPy.

US-based core analytical platform Vertica has announced the release of Vertica 11 Analytics Platform at Vertica Unify 2021.

The platform has major features and enhancements to deliver unified analytics and machine learning across multi-cloud and multi-regional deployments with self-service container workflows to meet the agility, speed, and security requirements of analytic driven organisations.

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“Unified Analytics is a critical movement in our industry. But truly unified analytics requires proven and mature security, true deployment choice, end-to-end machine learning in production, and no-compromise analytical performance for organisations to capitalise on this megatrend,” said Colin Mahony, Senior Vice President and General Manager, Vertica, Micro Focus. 

“In Vertica 11, we expanded Vertica in Eon Mode to the Azure cloud, delivered support for Docker containers and Kubernetes, extended our market lead in advanced analytics and machine learning including time series forecasting, and much more. The feature list goes on and on – Vertica 11 is truly the unified analytics platform with the fastest performance at unlimited scale,” Colin added.

Vertica 11 includes more in-database machine learning capabilities with the latest release of VerticaPy, an open-source Python library for Vertica that supports Python projects on data stored in Vertica. VerticaPy contains expanded machine learning functionality, connection, and data exploration capabilities as well as graphical capabilities.

The release offers a new, open-sourced Apache Spark Connector that supports Spark 3.0 and Scala 2.12 with S3, SSO, and parallel read/write support, significantly improving performance. Additional key capabilities include an XG Boost algorithm, increased PMML integrations, and customised time series algorithms.

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