Vertica Announces Vertica 11, Delivering on Vision of Unified Analytics

Rhea-AI Summary

Vertica announced the launch of its Vertica 11 Analytics Platform at Vertica Unify 2021, enhancing unified analytics and machine learning capabilities across various cloud environments. Key features include expanded in-database machine learning functionality, improved security compliance with FIPS 140.2, and support for Docker and Kubernetes. Vertica 11 aims to offer organizations the flexibility to unify data siloes, with enhanced deployment options on Microsoft Azure, AWS, and Google Cloud. The platform also introduces advanced algorithms like XGBoost, strengthening its analytics performance.

Positive

• Launch of Vertica 11 enhances unified analytics and machine learning capabilities.
• Support for Docker and Kubernetes increases deployment flexibility.
• FIPS 140.2 compliance boosts security, appealing to federal clients.
• Expanded in-database machine learning functionalities provide better performance.
• Availability on major clouds including Microsoft Azure, AWS, and Google Cloud.

Negative

• None.

BOSTON, July 20, 2021 /PRNewswire/ -- At Vertica Unify 2021, Vertica announced the Vertica 11 Analytics Platform, which includes major features and enhancements to delivering 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 the most analytically driven organizations. With Vertica 11, organizations can unify their data siloes and choose from the broadest deployment options with improved automation capabilities to future-proof their analytics and machine learning to achieve measurable business value.

"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 organizations to capitalize on this mega trend," 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." 

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 now includes expanded machine learning functionality, connection, and data exploration capabilities as well as graphical capabilities. In addition, this 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 customized time series algorithms. 

"Running in-database analytics and machine learning will be a real game changer for Jaguar Racing," says Phil Charles, Technical Manager, Jaguar Racing. "With access to all the data, 700+ in-database functions, and the blazingly fast query results, Vertica helps us to make time-critical decisions to ultimately deliver an edge that leads to more points, podiums, and wins for Jaguar Racing."

With Vertica 11, Vertica in Eon Mode – Vertica's cloud-optimized architecture that separates compute from storage for rapid elasticity and better cost control -- now is in full production on Microsoft Azure cloud, in addition to AWS and Google Cloud. Vertica also welcomes Dell EMC ECS as a certified object storage partner for Eon Mode deployments for on-premises private data centers. Vertica now supports the Eon Mode database in a Kubernetes StatefulSet, further delivering on the commitment to deployment flexibility across multi-clouds and on-premises data centers.

Highlights and enhancements to Vertica 11 also include:

Broadest Deployment Support

• Eon Mode support for Microsoft Azure – Vertica in Eon Mode now officially supports Microsoft Azure Block Blob Storage, giving organizations complete freedom to choose proven, cloud-optimized architecture on all three major clouds.
• Docker Container and Kubernetes support – The Vertica-tested Docker image is now available on Dockerhub. With this support, organizations now have even more options for cloud-native deployments, with container and Kubernetes orchestration. Support for Vertica Kubernetes Operator, StatefulSets and Helm Charts is included.

Strengthened Security

• FIPS 140.2 compliance – Vertica complies with FIPS 140-2, which is used by Federal Agencies when organizations specify cryptographic-based security systems for protection of sensitive or valuable data.
• Improved Voltage integration – Improvements to the tight and seamless integration with Voltage SecureData ensure even more secure Format Preserving Encryption (FPE) of data, including data masking and format preserving hash.
• Simplified security configurations – Vertica has considerably simplified security processes to make it easier and more streamlined to restrict and grant user and group privileges

End-to-End Machine Learning

• Expanded Time Series support – Time series forecasting is expanded greatly to include support for autoregression, moving average, stationarity tests, and automatic generation of correlation plots in-database using SQL and VerticaPy.
• Spark 2.0 Connector – Vertica has contributed an improved connection with Spark that now supports Spark 3.0 and 3.1 with more efficient bi-directional data flows, Projections and filters, SQL push-down, and enterprise SSO support, including Kerberos.
• VerticaPy - VerticaPy is a new open source Python library that exposes Pandas and Scikit-like functionality to conduct data science projects on data stored in Vertica, combining the scalability of Vertica with the flexibility of Python.
• AutoML - VerticaPy Delphi, our most advanced auto-ML capability yet, can auto-prepare data, train and evaluate several algorithms, and display a graph by accuracy and efficiency within minutes, using full Vertica data sets to vastly shorten development time for machine learning and AI projects.
• XGBoost - XGBoost is the latest algorithm added to the long list of in-database algorithms supported by Vertica. The Auto-Retrain meta function ensures that models consistently produce accurate predictions.
• Expanded Deep Learning and PMML support – Vertica now supports import of the latest version of TensorFlow, version 2.5, deep learning and custom models. Generalized linear model import from PMML is also supported.

Increased Analytical Performance and Much More

• Stored Procedures – Vertica 11 introduces stored procedures for the purpose of automating the information lifecycle from ELT, through data preparation, to the ML pipeline. Vertica has a rich set of functions at each step in the lifecycle and usage pipeline. Stored procedures will enable users to automate their execution and facilitate metadata collection for auditing and forensics.
• Expanded Complex Data Type support – Analysis of complex data types such as Maps, Arrays, and Structs is now expanded with the improved ability to export data in these forms directly to ORC as well as Parquet, and a complete capability to query files with complex types in place, without modification or import.
• Management Console (MC) enhancements – The MC has several improvements, including quick launch templates to get you working faster, simplified workflows to help you work more efficiently, and customizable alerts and monitoring metrics to keep your Vertica cluster running smoothly.
• Query Optimization improvements – The speed boost in any query containing a WITH clause will show the clear difference in the ongoing query optimization engine improvements. 

Additional Information
For more information about Vertica 11, please visit www.vertica.com.

To learn more about Vertica on Twitter, please follow @VerticaUnified and join Vertica on LinkedIn and Facebook.

About Vertica
The core analytical platform within the Micro Focus software portfolio, Vertica is the Unified Analytics Platform, based on a massively scalable architecture with the broadest set of analytical capabilities and end-to-end in-database machine learning. Vertica enables many customers – from Philips to The Trade Desk to MassMutual to many others – to easily apply these powerful functions to the largest and most demanding analytical workloads, arming businesses and its customers with predictive business insights faster than any data analytical platform in the market. Vertica provides its Unified Analytics Platform across all major public clouds and on-premises data centers and integrates data in cloud object storage.

Contact: Lauren Warble, microfocus@pancomm.com

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SOURCE Micro Focus

FAQ

What is the Vertica 11 Analytics Platform?

The Vertica 11 Analytics Platform is an enhanced version that provides unified analytics and machine learning capabilities across multi-cloud deployments.

When was Vertica 11 announced?

Vertica 11 was announced on July 20, 2021, during the Vertica Unify 2021 event.

What new features does Vertica 11 offer?

New features include enhanced in-database machine learning, Docker and Kubernetes support, and compliance with FIPS 140.2 for security.

How does Vertica 11 improve data security?

Vertica 11 complies with FIPS 140.2 and includes improved integration with Voltage SecureData for enhanced data protection.

On which cloud services is Vertica 11 available?

Vertica 11 is available on Microsoft Azure, AWS, and Google Cloud.