Neo4j
Overview
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HQ Location
United States
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Year Founded
2007
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Company Type
Private
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Revenue
$10-100m
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Employees
201 - 1,000
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Website
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Twitter Handle
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Company Description
Neo4j is the graph company behind the #1 platform for connected data. The Neo4j graph platform helps organizations make sense of their data by revealing how people, processes and digital systems are interrelated. This connections-first approach powers intelligent applications tackling challenges such as Artificial Intelligence, fraud detection, real-time recommendations and master data. The company boasts the world's largest dedicated investment in native graph technology, has amassed more than ten million downloads, and has a huge developer community deploying graph applications around the globe. More than 250 commercial customers, including global enterprises like Walmart, Comcast, Cisco, eBay and UBS use Neo4j to create a competitive advantage from connections in their data. Neo4j is privately held and funded by Eight Roads Ventures (an investment arm of Fidelity International Limited), Sunstone Capital, Conor Venture Partners, Creandum, Dawn Capital and Greenbridge Investment Partners. Headquartered in San Mateo, Calif., Neo4j has regional offices in Sweden, Germany and the UK. For more information, please visit Neo4j.com and @Neo4j. All trademarks and registered trademarks, including Neo4j? are the property of their respective owners.
IoT Solutions
What is Neo4j
Neo4j is a highly scalable native graph database, purpose-built to leverage not only data but also data relationships.
Using Neo4j, developers build intelligent applications that traverse today's large, interconnected datasets in real time. Powered by a native graph storage and processing engine, Neo4j delivers an intuitive, flexible and secure database for unique, actionable insights.
Neo4j is a highly scalable native graph database, purpose-built to leverage not only data but also data relationships.
Using Neo4j, developers build intelligent applications that traverse today's large, interconnected datasets in real time. Powered by a native graph storage and processing engine, Neo4j delivers an intuitive, flexible and secure database for unique, actionable insights.
Key Customers
Vanguard, Airbnb, Microsoft, Hp, Cisco, IBM, Lockhead Martin, Bayer, Vanguard
IoT Snapshot
Neo4j is a provider of Industrial IoT infrastructure as a service (iaas), platform as a service (paas), application infrastructure and middleware, analytics and modeling, functional applications, and cybersecurity and privacy technologies, and also active in the finance and insurance, and healthcare and hospitals industries.
Technologies
Use Cases
Functional Areas
Industries
Services
Technology Stack
Neo4j’s Technology Stack maps Neo4j’s participation in the infrastructure as a service (iaas), platform as a service (paas), application infrastructure and middleware, analytics and modeling, functional applications, and cybersecurity and privacy IoT Technology stack.
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Devices Layer
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Edge Layer
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Cloud Layer
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Application Layer
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Supporting Technologies
Technological Capability:
None
Minor
Moderate
Strong
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Case Studies.
Case Study
Data Lineage Tool Improves Risk Management, Drives Compliance
UBS needed to comply with regulations put in place to strengthen systems for risk data aggregation and internal risk reporting in the wake of the 2007 global financial crisis. Specifically, UBS sought compliance with the Basel Committee on Banking Supervision issued standard 239 (BCBS 239).UBS built an application called Group Data Dictionary (GDD) as its data lineage and data governance tool.The first iteration was built on Oracle, but UBS soon discovered limitations with an RDBMS approach, which relies on JOINS to connect data across tables. UBS decided it needed a better solution suited to creating real-time data lineage visualizations and exporting lineage information for ad-hoc analysis via Excel.
Case Study
Graph Technology Powers Cybersecurity Situational Awareness
Cybersecurity researchers at MITRE needed to go beyond rudimentary assessments of security posture and attack response. Doing so required merging isolated data into higher-level knowledge of network-wide attack vulnerabilities and mission readiness.Noel and his team also struggled with fully comprehending a given security environment and mapping all known vulnerabilities. Specifically, these goals demanded a flexible architecture that accommodated advanced analytics, ad hoc queries and graph visualization, all of which they then lacked.
Case Study
Novartis Captures the Latest Biological Knowledge for Drug Discovery
Novartis faced the challenge of combining its historical data stores with this burgeoning phenotypic data. They also needed a way to place all this data within the larger context of ongoing medical research from around the world. The Novartis team wanted to combine its data with medical information from NIH’s PubMed. PubMed contains about 25 million abstracts from some 5,600 scientific journals.The Novartis team sought a way to empower researchers to ask questions connecting the dots between all of this data in the context of the latest medical research.
Case Study
Transforms & Accelerates Customer Engagement
They had limited visibility of what they had delivered before, they needed to do more than simply list everything in a database. Wanted to be able to map and match capabilities onto what they were hearing from the client, and what they were saying in their strategy papers and company reports, to present the ideal recommendation and create the most effective transformation roadmap – and do this in real-time, in client meetings.
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