Latest Micro Focus release empowers organisations with greater data insights
Micro Focus has released the Vertica 10 Analytics Platform, delivering a range of updates to enable machine learning and unified predictive analytics at scale.
The updates also expand deployment options for Vertica in Eon Mode, which offers intensive, variable workloads across major cloud and on-premises data centers.
The latest release brings deeper integration with Python and TensorFlow for unsupervised learning and PMML standard model format for cross-platform compatibility.
As such, data scientists can continue using Python and TensorFlow while leveraging larger volumes of data and parallelised performance advantages, Micro Focus says.
Furthermore, Vertica 10 expands deployment and communal storage options for Vertica in Eon Mode. This expands public cloud support for Google Cloud Platform (GCP) and Apache Hadoop HDFS as communal storage.
Following support for Vertica in Eon Mode for Pure Storage FlashBlade, updates to Vertica in Eon Mode for HDFS and MinIO now include more choices for organisations to manage their dynamic workloads with S3 object stores in on-premises and cloud environments, Micro Focus states.
The expansion of Vertica in Eon Mode is currently available on AWS and now on GCP.
Other top enhancements include new migration functionality, database designer, security improvements, greater capabilities around machine learning at scale, and the ability to analyse data in any format.
According to Micro Focus, new migration functionality enables seamless migration for customers moving from Vertica in Enterprise Mode to Vertica in Eon Mode to adopt the next-generation data architecture separating compute from storage for on-premises, hybrid, and cloud deployments.
The updated Vertica Database Designer offers improvements to operations and ease of use and reduces resource usage by orders of magnitude, also improving projection designs for faster queries, the company states.
The company also highlights that Vertica 10 includes security enhancements that include the process of administering TLS certificates, user authentication and permissions management with LDAP Link, Kerberos for Vertica-Python and new permissions system tables, and improved support for format preserving encryption with new Voltage integration capabilities.
To operationalise machine learning at scale, Vertica 10 imports models built in other platforms and languages including Spark, Python, and SPSS using the PMML format. With PMML model export, models built in Vertica can also be exported for scoring in other systems such as edge nodes for IoT use cases.
Organisations can also now put Neural Networks and custom machine learning models into production by importing pre-trained TensorFlow models into Vertica for predictions on hot data and archiving for replicability.
When it comes to data, organisations can analyse complex data types from MAPS and ARRAYS to STRUCTS in Parquet on S3 or HDFS to open SQL-based analytics to new use cases, according to Micro Focus.
Micro Focus states the top benefits of Vertica 10 is that it enables organisations to unify data silos and take advantage of deployment models, leading to a greater ability to monetise exponential data growth and capture business opportunities.
Micro Focus senior vice president and general manager of Vertica, Colin Mahony, says, “Vertica 10 expands the options for a unified analytics strategy to address growing data silos, a mix of cloud, on-premises, and hybrid environments, and the pressing need to operationalise machine learning at scale.
He says the focus of the new updates are on giving businesses greater means to gain insights from data.
Mahony says, “Over the years, many organisations have successfully captured massive amounts of data, but are now challenged with getting the business insights they need to become data-driven.
"In addition, the market demand to leverage cloud architectures separating compute from storage needs to be balanced with the higher costs and increased risk of cloud-only data warehouses, while machine learning projects with tremendous potential have struggled to make their way into production.
Vertica 10 will be available in the coming weeks to customers worldwide for trial or purchase.
It is available to deploy on Google Cloud Platform as a bring-your-own license (BYOL) option. In the future, it will be offered by-the-hour on the Google Marketplace.