Neo4j and Microsoft Azure are excited to bring you the most powerful, scalable, and secure graph data science technology with Neo4j AuraDS Enterprise, now available on Microsoft Azure in the Early Access Program. With this new partnership, data scientists can easily gain insights from their data and leverage graph algorithms and embeddings to explore billions of data points in seconds, all in the cloud.
What Is Neo4j AuraDS Enterprise?
Neo4j AuraDS Enterprise is a fully managed graph data science cloud service. It takes care of all infrastructure administration so that data scientists can focus on analyzing data and getting ML models into production. With over 65 pre-tuned graph algorithms and ML models, data scientists can easily identify and interpret meaningful relationships in their data and generate compelling visualizations to make informed decisions.
Businesses and organizations can leverage graph data science to discover what’s important, unusual, and what’s next. Recommendation engines, anomaly and fraud detection, route optimization, customer 360, and network analysis are just a few examples of projects that can take advantage of graph data science.
How Does AuraDS Work With Microsoft Azure?
With Neo4j AuraDS Enterprise on Microsoft Azure, you can integrate, analyze, and manage your graph data science pipelines using Azure Machine Learning and Azure Synapse Analytics. Our partnership with Microsoft Azure opens up new possibilities to leverage the wider Azure ecosystem, allowing enterprises to create value and achieve their goals with ease quickly.
As a Microsoft Azure Partner Network member, we help organizations make the most of their data connections, influences, and relationships. With a single SaaS license that covers all aspects of the infrastructure, including storage (and backup storage), IO rate, data transfer, and more, it’s easy for any enterprise data science team to get started and create value quickly.
To learn more about how Neo4j AuraDS Enterprise can bring an uplift to model accuracy with graph features, sign up for Early Access to get started.