Neo4j’s desire to offer solutions aimed at data scientists is no secret. In the columns of MagIT, Emil Eifrem, CEO of Neo4j, argued that the development of artificial intelligence offered significant growth prospects for his company.
In this sense, the publisher launched a data processing platform two years ago, under the name of graph data Science (GDS). Its fully managed distribution, accessible since April 12, 2022, is called AuraDS. It is based on the newly available version 2.0 of GDS and on the NoSQL Neo4j DBMS. Everything is hosted on Google Cloud Platform (GCP).
AuraDS or Graph Data Science on demand
AuraDS encapsulates the enterprise edition of Graph Data Science. Like GDS, AuraDS includes more than 65 graph algorithms associated with a Python client. These tools should make it possible to develop machine learning and analytical use cases such as fraud detection, route optimization, product recommendation, or even customer knowledge.
In its documentation, the editor specifies that the tool provides the means to prepare the data, to train the models from pre-trained algorithms and to deploy them in production.
With AuraDS, Neo4j intends to simplify the work of data scientists by offering them a drag-and-drop interface for loading data (from a CSV file or the AuraDB import utility), modeling them in graphs (thanks to the data viz Bloom tool) and configure the processing flows.
Like GDS 2.0, the platform has a catalog dedicated to models, and another for processing pipelines. Indeed, there are two types of algorithms and therefore two calculation methods with this tool: the first are used to process the data linked to the nodes of a graph, the second to the edges which connect the nodes.
In addition, AuraDS supports Neo4j’s Apache Spark and Kafka connectors to process data in batch or streaming.
Managed version obliges, the publisher offers to automate the control of workloads, patches and backups as well as the updates of this product. An MLOps function should automate the management of model backups and restores. Data is encrypted at rest and in transit, while all backups are kept for 180 days.
Neo4j provides access to two types of instances: those in execution, and those in pause. A paused instance would reduce costs by 80% compared to a running one.
The pay-as-you-go business model relies on a “self-start” third party, billed pro-rated on monthly consumption, starting at $0.125 per GB of RAM per hour and $0.025 cents per GB of RAM per hour for paused instances. AuraDS Enterprise is available in preview after signing an annual contract.
Where the enterprise edition of GDS supports an “unlimited” amount of storage space, RAM and vCPUs, AuraDS provides access to instances comprising between 8 and 96 GB of RAM, between 2 and 20 vCPUs as well as only between 16 GB and 192 GB of storage space.
AuraDS Enterprise will push two of these limits to 256 GB of RAM and 40 vCPUs. Note that, unlike AuraDS, this Enterprise version is not multi-tenant. It must be deployed behind a specific VPC.
A SaaS platform, but not serverless
The choice of RAM as the primary unit of measurement is no coincidence: with Neo4j, data graphs reside in-memory. However, customers cannot decide precisely how much RAM or compute they would need.
With AuraDS, there are seven instances of different sizes. An instance with 2 vCPUs, 8 GB of RAM and 16 GB of storage costs $1 per hour (and 20 cents on break). The price increases by 1 dollar per hour (and therefore by 20 cents when the instances are paused) between the first four instances. This price difference increases to 2 dollars (and 40 cents on break) per hour between the fifth and sixth instance. The best endowed instance (20 vCPU, 96 GB of RAM, 192 GB of storage space) costs 12 dollars per hour and 2.40 dollars in pause. Neo4J does not specify whether it is possible to stop an instance without losing backups linked to workloads. In addition, the publisher does not guarantee an SLA. However, subscribing to AuraDS Enterprise will allow you to negotiate terms of service and obtain volume discounts.
Neo4j pampers its partnership with Google Cloud
It is possible to pay and receive the invoice via the AuraDS console or the Google Cloud console from the Marketplace. This second option resulting from the privileged partnership between Neo4j and GCP allows customers of the cloud provider to subscribe to the data science service with their credits obtained on commitment of use.
Precisely, AuraDS can be integrated with Vertex AI for data science teams who have decided to administer their processing pipelines from the GCP development environment.
However, this exclusivity of AuraDS on GCP is temporary. The publisher hopes to offer this SaaS product on AWS, then on Azure, just as it plans to do for AuraDB Enterprise.
Especially since Neo4j is not the first to offer a similar service: its young competitor TigerGraph had launched its offer in April 2021 on GCP.
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AuraDS: Neo4j draws its data science platform in SaaS mode
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