Neo4j has unveiled AuraDS, a managed data science service comprising various tools for experts and developers. It is built on AuraDB and is available on Google Cloud Platform.
In a desire to help AI experts and developers who wish to embark on AI projects, Neo4j has just launched a specific managed service, called AuraDS, it offers a catalog of graph algorithms, machine learning pipelines and data science methodologies. According to the editor, to meet their growing needs, most companies need to develop AI-based applications, but they do not have the time or resources to tackle complex data engineering tasks. , which delays the entire process of developing and deploying next-generation applications. “Built around Neo4j’s AuraDB cloud database, the AuraDS service can reduce the build time of these AI-powered applications,” Neo4j explained.
The resurgence of graph-oriented databases
“Graph databases are particularly useful for modeling social relationships, sales or services,” said Holger Mueller, principal analyst at Constellation Research. Neo4j is not the only graph-oriented database. This is also the case with Amazon Neptune, TigerGraph and AnzoGraph. “The graph is more flexible and richer in information than traditional relational databases, which became the majority a few years ago. But graph-oriented ones are making a strong comeback,” added the analyst.
“AuraDS takes all the inherent advantages of a graph-based database and applies them to the data pipelines that power machine learning models,” Mueller added. However, the analyst clarified that this process was cumbersome and had to work perfectly. The latter also believes that similar technologies are attracting growing interest and that the recent announcement of the takeover of DBaaS specialist Instaclustr by NetApp is a step in this direction.
A set of tools
Among the features of AuraDS, Neoj4 mentioned automated operations, support for MLops, and one-click backup. The platform can extract meaning from relationships between data through 65 graph algorithms in a single workspace, all in a drag-and-drop user interface to model and import data into a graph. According to the publisher, it is possible to monitor, correct and automatically save workloads, as well as restore models.
“The fully managed service, which offers a pay-as-you-go pricing model with the ability to pause unused instances, offers to scale compute resources up or down on demand, and offers data scientists to back up instances , models, and in-memory graphs with a single click,” Neo4j said. For now, AuraDS is only available on Google Cloud Platform.