Neo4j’s New AuraDS Brings Managed Data Science Services to Google Cloud

Neo4j has released a new managed cloud service called AuraDS that aims to accelerate data science engineering practices for businesses by providing a library of graphing algorithms, machine learning pipelines and data science methodologies.

Most enterprises need to develop intelligent software for growing business needs, but they lack the time and resources to tackle complex data engineering tasks, slowing down the entire process of developing and deploying next-gen applications, the company said.

The new AuraDS service, built around Neo4j’s cloud-based AuraDB, is designed to reduce the time it takes to build these intelligent applications, the company said.

Chart databases are especially useful when it comes to modeling social, sales, or service relationships, said Holger Mueller, principal analyst at Constellation Research. In addition to Neo4j, Graph databases include Amazon Neptune, TigerGraph, and AnzoGraph.

“Graph is more flexible and richer in information than the traditional relational databases that existed a few years ago. Graph databases are now making a comeback,” Mueller added.

AuraDS takes the inherent advantages of a graphical database and applies it to data pipelines that can feed machine learning models, Mueller said. However, the analyst said this process is cumbersome and must be seamless.

Mueller also believes there is growing interest in similar technologies and NetApp’s recent announcement of its intention to put Instaclustr, the data and workflow application-as-a-service provider, in the same category.

Features of AuraDS include automated operations, MLops support and one-click backup, Neo4j said. In addition to providing a platform to extract meaning from data relationships through 65 graphing algorithms in a single workspace, AuraDS provides a drag-and-drop user interface to model and import data into a graph.

It has the ability to automatically monitor, patch and backup workloads, along with the ability to restore models, the company said. The fully managed service, which offers a pay-as-you-go pricing model with the option to pause unused instances, comes with the option to scale up or down compute resources on demand and enables data scientists to back up of instances, models, in-memory graphs with a single click, the company said.

At the moment, AuraDS is only available on Google Cloud Platform.

Copyright © 2022 IDG Communications, Inc.


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