Neo4j and Google Cloud Extend Strategic Partnership With New Native Integration to Google Cloud's BigQuery Cloud Data Warehouse
Neo4j has expanded its strategic partnership with Google Cloud by introducing a native integration with Google Cloud's BigQuery. This integration allows users to seamlessly combine SQL analysis with graph-native data science and machine learning. Customers can now conduct deep graph analysis and move data models between BigQuery and Neo4j Graph Data Science easily. This partnership aims to enhance analytical capabilities and decision-making by utilizing graph technology, projected to be crucial in 80% of data innovations by 2025 according to Gartner. The integration is currently in private preview, with general availability expected in August 2023.
- New native integration with Google Cloud's BigQuery enhances analytical capabilities.
- Customers can seamlessly conduct graph analysis using SQL and Neo4j Graph Data Science.
- Integration expected to facilitate better AI predictions and improve decision-making.
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Integration of both market-leading systems helps customers gather deeper analytical insights and expand problem-solving abilities using graph data science workloads
The Google Cloud BigQuery integration enables users to conduct deep graph analysis of connected data, in-memory within Neo4j, and return results to BigQuery for use in downstream models and analysis. This means that customers can build graph data models in BigQuery and move them directly into Neo4j Graph Data Science in a few simple steps, eliminating the need for extra software or data staged in a queuing system. Additionally, data engineers can work entirely within BigQuery to build models for deep graph analysis in Neo4j Graph Data Science.
This latest partnership milestone comes as graph databases and graph data science technology are dramatically accelerating advances in artificial intelligence and machine learning, helping enterprises find hidden relationships and patterns across billions of data connections deeply, easily, and quickly. According to Gartner, graph technologies will be used in
"As graph technology continues to advance, we are excited about expanding our partnership with Neo4j to introduce this new integration with Google BigQuery. The powerful combination of Graph Data Science with BigQuery will enable customers to solve even more complex problems, with the ability to conduct deep graph analysis of connected data with a seamless experience. We are excited to bring these innovations to market, together with Neo4j." said
Emil Eifrem, CEO and Co-founder of Neo4j said, "Data scientists can now make better AI predictions thanks to Neo4j's integration with Google Cloud's BigQuery. Graph-powered AI has changed the landscape for intelligent applications and large language models (LLM), improving their accuracy and unlocking new use case possibilities with graph algorithms and graph visualization. We're excited by what we can enable for our customers together with this latest milestone."
"We chose Neo4j Graph Data Science on AuraDS because it is a completely managed, cloud-based infrastructure combined with an elegant and user-friendly set of tools and extensive library of production-ready data science algorithms that gives us confidence in our platform and allows us to focus on our data and application development," said
Long-standing strategic partnership since 2019
Google Cloud and Neo4j launched their strategic partnership in 2019, with Neo4j becoming Google Cloud's first graph database partner. The objective was to ensure businesses have more seamless access and insights into the data required for digital transformation. The partnership included integration with Vertex AI, an ML development platform, enabling enterprises to build and deploy improved graph-based machine learning models. The relationship also benefited customers who complemented Neo4j Graph Database with data from Google Cloud's Enterprise Knowledge Graph to provide more complete information. Hundreds of large enterprises and SMBs, such as Monsanto, Lucinity, PwC Canada, and more around the world, have leveraged Neo4j on Google Cloud for use cases such as anti-money laundering, customer engagement, identity and access management, and more.
A Neo4j demo is also available, showing a use case of shipping networks and freight movement through a global system of airports. By pushing data seamlessly from BigQuery within Neo4j Graph Data Science and ML, the connections between the business process and the physical world were easily identified, highlighting inefficiencies (i.e. high operational loads and cargo bottlenecks), quantifying risk, and pinpointing regional interdependencies.
The connector is currently available via private preview within Google Cloud and is targeted for general availability from
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About Neo4j
Neo4j, the Graph Database & Analytics leader, helps organizations find hidden relationships and patterns across billions of data connections deeply, easily and quickly. Customers leverage the structure of their connected data to reveal new ways of solving their most pressing business problems, from fraud detection, customer 360, knowledge graphs, supply chain, personalization, IoT, network management, and more – even as their data grows. Neo4j's full graph stack delivers powerful native graph storage, data science, advanced analytics, and visualization, with enterprise-grade security controls, scalable architecture and ACID compliance. Neo4j's community of data leaders comprises a vibrant, open-source community of more than 250,000 developers, data scientists, and architects across hundreds of Fortune 500 companies, government agencies and NGOs. Visit neo4j.com.
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