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Advances in Cloud Deployment, Security, Operations, Driver Support and User Experience
accelerate adoption of Neo4j for enterprises everywhere.
GraphGrid Virtual Private Cloud (GraphGrid VPC) guarantees a logically isolated section of the GraphGrid Cloud where we launch all your GDP resources in a virtual network only you can access.
The configuration of the VPC is optimized with security in mind. For example, a public-facing subnet is created for your servers that require access to the Internet, and your backend systems in a private-facing subnet with no Internet access. GDP leverages multiple layers of security, including security groups and network access control lists, to help control access to your GDP clusters.
Additionally, you can create a Direct or Peering VPN connection between your corporate datacenter or VPC and your GDP to leverage the GDP as an extension of your existing data centers.
GraphGrid Data Platform provides centralized enterprise services for comprehensive security to enable end-to-end protection, authorized access, compliance and auditing of data in motion and at rest.
Protect: End to end security layers for At-Rest and In-Flight data including masking and encryption.
Access: Ensure appropriate data access controls and appropriate authentication and authorization mechanisms.
Comply: Ensure appropriate regulatory compliance.
Audit: Provide accountability for auditors to control and verify protection and compliance.
GraphGrid Data Platform provides centralized enterprise services for consistent operations to provision, manage, monitor and deploy Neo4j clusters.
Provision: Create Neo4j clusters on demand using established, configured, repeatable processes.
Manage: A unified dashboard to efficiently manage all cluster and data operations.
Monitor: Detailed metrics to provide real-time monitoring with configurable cluster activity views.
Deploy: Automated cluster deployment across multiple geographical regions worldwide.
GraphGrid Data Platform provides centralized enterprise services for trusted data governance to enable reliable integration, data preparation, and repeatable policy-based workflows.
Integrate: Ingest, organize and monitor data effectively to increase integrity and trust.
Prepare: Cleanse, validate, profile and manage data with predictability to increase quality.
Repeat: Recreate the relevant data landscape at a given point in time to increase reliability and recoverability.