Micro Focus Introduces Vertica 9

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Unified advanced analytics database features advancements in in-database Machine Learning, direct querying of Parquet data on AWS S3, support for Google Cloud Platform and Azure Power BI, and beta release of cloud optimised separation of compute and storage

Micro Focus has announced a major release of its Vertica Analytics Platform. Vertica 9 introduces an extended list of in-database Machine Learning capabilities – including new algorithms, model replication, data preparation functions, and continuous end-to-end workflow – to simplify the production and deployment of machine learning models. In addition, Vertica 9 will be available for deployment in the Google Marketplace and has further integration with Microsoft Azure including Power BI certification. With Vertica 9, organisations can now analyse their data not only in place, but now in the right place – without data movement – while supporting any major cloud deployment for fast and reliable read and write for multiple data formats.

Micro Focus also announced the beta release of Vertica in Eon Mode, which enables organisations to evaluate the separation of compute and storage for Amazon Web Services (AWS) deployments. Companies in the AWS ecosystem will be able to leverage AWS S3 for storage and Vertica’s query-optimised analytics engine for processing speed to capitalise on cloud economics.

Legacy data warehouse solutions have forced many enterprises into rigid and high-cost proprietary hardware and analytics solutions supporting only limited data formats. As data formats and storage locations continuously evolve, organisations require a powerful and unified solution to analyse data in the right place at the right time, with the performance and economics that the business requires.

“Data is a one of the most valuable assets for companies, and a company’s ability to monetise their data while optimising for both cost and performance at scale is already a fundamental differentiator in every industry,” Darren Ong, Vice President, Asia Pacific and Japan, Vertica, Micro Focus. “Vertica’s ability to analyse an extensive set of data formats in the right place, at the right time, enables our customers to optimise for both cloud economics and user demands. Vertica is the only platform in the industry that can provide high-performance advanced analytics and in-database machine learning with true freedom from underlying infrastructure across the full data pipeline, at the scale demanded by the world’s most data-driven organisations.”

Vertica 9: Delivering High-Performance In-Database Machine Learning and Advanced Analytics Anywhere, Anytime, on Any Major Cloud

Critical to Micro Focus providing customers with enterprise-grade scalable software with analytics built in, Vertica provides organisations with a single, unified analytical database that supports all major cloud platforms, all popular data formats, enhanced integrations with Spark and Kafka and an analyse-in-place, unified architecture that enables businesses to monetise their data assets with cloud elasticity – regardless of data location. Organisations can use Vertica 9’s flexible and expanded deployment options across on-premise, private, and public clouds, and on Hadoop and AWS S3 data lakes, to adopt a best-fit analytical solution. This affords them the broadest choices on where, how, and when they run analytics – supported by new provisioning and administrative UIs built specifically for the cloud.

“Fidelis has the first and only purpose-built, automated detection and response platform that delivers 10-20x efficiency for security operations teams. Our unwavering goal is to automate cyber defense action with intelligence – and Machine Learning for predictive analytics is the key,” said Abhishek Sharma, Data Scientist at Fidelis Cybersecurity. “Vertica’s new in-database machine learning capabilities are like gold! We are extremely excited to train our Machine Learning models on our data in Vertica and ship them with our platform to run on our customers’ clusters. This is something that is much harder with any other tool. Vertica’s in-database machine learning will improve our ability to offer new predictive analytics features quickly and easily to our growing customer base. It will improve our competitive positioning.”

Beta Version of Vertica Eon Mode for Cloud Economics

Vertica’s beta release of its new Eon Mode architecture, offering separation of compute and storage, provides rapid elastic scaling up and down on the Vertica cluster, with just-in-time workload-based provisioning. An intelligent, new caching mechanism on the nodes enable organisations to benefit from Vertica’s industry-leading query performance. Companies in the AWS ecosystem will be able to leverage AWS S3 for storage and Vertica’s query-optimised analytics engine for processing speed to capitalise on cloud economics.

New Support for Google Cloud Platform

Vertica for Google Cloud Platform support will be available via the Google Marketplace, giving organisations the flexibility and freedom to choose yet another leading cloud platform for their needs.         

Performance and Scalability Enhancements

The new release triples load performance, dramatically increases query performance with Flattened Tables, and extends concurrency by up to 60 percent. In addition, Vertica 9 natively integrates with key ecosystem technologies and open source innovation, including Microsoft PowerBI, Cloudera Manager and Apache Spark 2.1.

Highlights and enhancements to Vertica 9 include:

  • In-Database Machine Learning – Provides a comprehensive set of new Machine Learning algorithms for categorisation, overfitting and prediction to enhance processing speed by eliminating the need for down-sampling and data movement.
    • Support for new data-preparation functions for deriving greater meaning from the data, while improving the quality of analysis.
    • Streamlined end-to-end workflow simplifies production deployment of Machine models – particularly for customers that embed Vertica and require the ability to replicate models across clusters.
  • Improved Core Data Management and High Analytical Performance – Reflects continual investments in the core underlying database architecture, including greater management of massive amounts of historical data with hierarchical partition management and more consistently high performance under the most demanding workloads with the most sophisticated analytical queries.
  • Parquet Writer – Introduces a new HDFS Parquet writer – built on Vertica’s fast and reliable ability to not only read, but now write data and results on HDFS – to derive and contribute immediate insights on growing data lakes in an organisations’ Hadoop data pipeline.
  • Flattened Tables – Facilitates the task of performing complex JOINs across multiple tables much less cumbersome and much more performant. Analysts can quickly write straight-forward, fast-running queries as if the data resided in one big flat table without the need to alter their existing schemas, simplifying and speeding the process and management of big data analytics in databases with complex schemas.

Vertica 9 will be generally available in October 2017.

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