This site is not optimized for Internet Explorer 9 and lower. Please choose another browser or upgrade your existing browser in order get the best experience of this website.
GraphGrid Data Platform
The Internet-Scale Graph Data Platform
GraphGrid Connected Data Platform uses a connections first approach to data. Providing the full suite of essential connected data capabilities that are required by the enterprise and that serve as the foundational data platform capability for artificial intelligence (AI) and machine learning (ML). This comprehensive set of capabilities is aligned to the following functional areas: Data Management, Data Access, Data Integration, Security, Operations, Application Integration and Deployment Strategy. Available on-demand is the GraphGrid Graph Database Service (GDS) with Open Neo4j Enterprise Engine
GraphCompute & DataMate: The core of GraphGrid
The core components of GraphGrid Data Platform are GraphCompute and DataMate. GraphCompute is the architectural ring around Neo4j that enables you to process data simultaneously in multiple ways. GraphCompute provides the resource management and pluggable architecture for enabling a wide variety of data access methods. DataMate provides the scalable, fault-tolerant, efficient storage and routing for big data.
Access data from a variety of engines
GraphCompute provides the foundation for a versatile range of processing engines that empower you to interact with the same data in multiple ways, at the same time. This means applications can interact with the data in the best way: from batch to interactive CQL or low latency access directly on the graph with the Java Traversal API. Emerging use cases for data science and search are also supported with Apache Spark GraphX and ElasticSearch.
Load and manage data according to policy:
GraphGrid Data Platform extends data access and management with powerful tools for data governance and integration. They provide a reliable, repeatable, and simple framework for managing the flow of data in and out of Neo4j. This control structure, along with a set of tooling to ease and automate the application of schema or metadata on sources is critical for successful integration of Neo4j into your modern graph data architecture.
Authentication, Authorization, & Data Protection:
Security is woven and integrated into GraphGrid Data Platform (GDP) in multiple layers. Critical features for authentication, authorization, accountability and data protection are in place so that you can secure GDP across these key requirements. Consistent in approach throughout all of the enterprise Neo4j capabilities, GDP also ensures you can integrate and extend your current security solutions to provide a single, consistent, secure umbrella over your modern graph data architecture.
Provision, manage, monitor and operate Neo4j clusters at scale:
Operations teams deploy, monitor and manage Neo4j clusters within their broader enterprise data ecosystem. GraphGrid Data Platform delivers a complete set of operational capabilities that provide both visibilities into the health of your cluster as well as tooling to manage configuration and optimize performance across all data access methods.
Integrates with your data analytics tools and App Tier
Neo4j has a thriving ecosystem of vendors providing additional capabilities and/or integration points. These partners contribute to and augment Neo4j with given functionality across Business Intelligence and Analytics, Data Management Tools and Infrastructure. Systems Integrators of all sizes are building skills to assist with integration and solution development.
Deploy on-premise or in the cloud:
GraphGrid Data Platform provides the broadest range of deployment options for Neo4j: from bare metal Linux to virtualized Cloud deployments. It is the most portable Neo4j distribution, allowing you to easily and reliably migrate from one deployment type to another. We also provide automated capabilities for backup to Amazon S3.