Micro Focus International plc-owned Vertica today announced a major update to its Vertica 10 Analytics Platform.

The platform now offers new features aimed at facilitating machine learning, plus more storage options for Vertica in Eon Mode, a version of the product that leverages elastic compute and scalable storage capabilities in the cloud.

The announcement came ahead of the Vertica Big Data Conference 2020, an annual user event that has been forced to go an all-digital format this week because of coronavirus pandemic restrictions.

Big-data aficionados will know all about Vertica. It’s a columnar storage platform that’s designed to handle large volumes of data and enables very fast query performance in traditionally intensive scenarios.

The platform was seen as a major disruptor during the early days of “big data.” That’s thanks to its improved query performance versus traditional database relational database systems, and its ability to provide high-availability and petabyte scalability on commodity enterprise servers.

In recent years, Vertica has had to contend with the rise of alternative analytics databases built on cloud-native architectures, such as Amazon Web Services Inc.’s RedShift and Snowflake Inc.’s eponymous offering.

But Micro Focus, which snapped up Vertica from its former parent company Hewlett-Packard Enterprise Co. in 2017, is hoping to reverse that trend with some new features in the platform that should give enterprises more options as they look to leverage machine learning and unify their data analytics strategies.

“Over the years, many organizations have successfully captured massive amounts of data, but are now challenged with getting the business insights they need to become data-driven,” said Colin Mahony, senior vice president and general manager of Vertica at Micro Focus. “Vertica 10 expands the options for a unified analytics strategy to address growing data siloes, a mix of cloud, on-premises, and hybrid environments, and the pressing need to operationalize machine learning at scale.”

Joy King, vice president of Vertica product management, marketing and education, told SiliconANGLE in an interview that the company is catering to data scientists through its closer integration with popular machine learning tools.

For example, Vertica 10 now offers deep integration with the TensorFlow machine learning framework and the Python programming language, enabling unsupervised learning and PMML standard model format. The idea is that data scientists can use the tools they’re familiar with alongside Vertica to leverage much larger volumes of data to improve the accuracy and replicability of their machine learning models.

“Several years ago, Vertica enabled machine learning algorithms to be run in SQL,” King said. “So we built in data prep, but there has been a lack of agreement on which tools are the right platform for machine learning.”

The company is also expanding Vertica in Eon Mode to the Google Cloud Platform, and updating Vertica in Eon Mode for the Hadoop Distributed File System, she said. The idea here is to help enterprises unify data sources, King said. The expansion of Vertica in Eon Mode means more deployment and communal storage options for users, giving enterprises more ways to manage dynamic workloads with object stores in on-premises and cloud environments.

“The trend is unifying all these data lakes with a single analytics database,” King said. “Sub-clustering allows them to allocate compute resources to various types of storage. It allows a lot more elasticity.”

King told SiliconANGLE the expanded capabilities in Vertica 10 gives the platform a significant advantage over competing products such as AWS RedShift and Google BigQuery, with one of the most important being the ability to avoid being locked in to a single vendor. “Most of our customers are looking for multicloud because they can’t risk lock-in,” she said.

Micro Focus said Vertica 10 will be made available to customers in the coming weeks.

With reporting from Robert Hof

Image: Vertica