List of Neo4j Graph Data Platform Customers
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Since 2010, our global team of researchers has been studying Neo4j Graph Data Platform customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Neo4j Graph Data Platform for Database Management from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Neo4j Graph Data Platform for Database Management include: Comcast, a United States based Communications organisation with 182000 employees and revenues of $123.73 billion, UBS, a Switzerland based Banking and Financial Services organisation with 106789 employees and revenues of $57.05 billion, Adobe, a United States based Professional Services organisation with 31360 employees and revenues of $23.77 billion, Woodside Energy, a Australia based Oil, Gas and Chemicals organisation with 4718 employees and revenues of $8.58 billion and many others.
Contact us if you need a completed and verified list of companies using Neo4j Graph Data Platform, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Neo4j Graph Data Platform customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Adobe | Professional Services | 31360 | $23.8B | United States | Neo4j | Neo4j Graph Data Platform | Database Management | 2018 | n/a |
In 2018, Adobe implemented the Neo4j Graph Data Platform to power Behance's activity feed infrastructure for its global creative community. This Database Management deployment focused on connected-data processing for real-time recommendations and activity feeds, operated from the United States and supporting Behance and related Adobe community features.
The implementation emphasized graph modeling of user relationships and activity, enabling real-time traversals and recommendation queries and a centralized feed generation capability. Neo4j Graph Data Platform was configured to handle event ingestion, graph query processing, and feed ranking workflows, reducing complexity in feed orchestration and lowering operational overhead for engineering teams.
Operational coverage centered on Behance product and community functions, improving onboarding flows and feed latency across global users. The deployment reduced storage footprint from approximately 50TB to around 40GB, and it explicitly lowered AWS spend by shrinking storage and compute requirements.
Governance and process changes consolidated feed processing into a graph-native data layer and simplified data access patterns to enable faster feature development for Behance and related Adobe community features. Documented outcomes include improved feed latency and onboarding, reduced operational overhead, and reduced infrastructure costs tied to storage and AWS spend.
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Comcast | Communications | 182000 | $123.7B | United States | Neo4j | Neo4j Graph Data Platform | Database Management | 2017 | n/a |
In 2017, Comcast implemented Neo4j Graph Data Platform within its Database Management environment to build the Xfinity profile graph for customer personalization and CRM. The initiative targeted the United States and focused on capturing richly connected household, person, device, and permission relationships to support xFi and smart-home experiences.
Comcast modeled nodes and relationships for household, person, device, and permission entities inside the Neo4j Graph Data Platform, creating a graph-based profile service that provided low-latency, multi-tenant user profiles. The implementation leveraged graph query and traversal patterns common to Database Management deployments to support personalized profile lookups and automation workflows.
The Neo4j Graph Data Platform centralized profile data across Xfinity applications and served xFi personalization and smart-home automation features such as Kidwatch and Porchcam, enabling faster product iteration. Operational coverage emphasized customer personalization and CRM, with the profile service consumed by product teams and application stacks across Xfinity.
Centralizing profiles in a graph service simplified governance and standardized permission and device relationship models, consolidating profile data to reduce fragmentation across Xfinity applications. The implementation used multi-tenant segmentation to maintain user isolation while exposing a unified profile surface for application integration.
As implemented, the graph-based profile service delivered low-latency, multi-tenant user profiles that enabled personalized automation features and faster product iteration while centralizing profile data across Xfinity applications. Comcast's use of Neo4j Graph Data Platform in Database Management directly supported customer personalization and CRM workflows.
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UBS | Banking and Financial Services | 106789 | $57.1B | Switzerland | Neo4j | Neo4j Graph Data Platform | Database Management | 2017 | n/a |
In 2017, UBS implemented Neo4j Graph Data Platform for its Group Data Dictionary. The Neo4j Graph Data Platform, categorized as Database Management, was synchronized with Oracle to deliver real-time data lineage and to support BCBS 239 driven risk, compliance, and data governance requirements in Europe.
Deployment focused on graph-based metadata modeling and interactive lineage visualization to map datasets, processes, and reporting flows. The implementation enabled interactive lineage diagrams and a real-time lineage capability that supported faster root-cause analysis for data quality and reporting. Functional capabilities emphasized metadata capture, relationship traversal, and visual exploration workflows consistent with Database Management platforms.
The Neo4j Graph Data Platform integrated with Oracle for source-system synchronization, enabling near real-time propagation of metadata changes into the Group Data Dictionary. Operational scope included risk, compliance, data governance, and reporting teams, with implementation serving data lineage and transparency use cases across the bank. The solution architecture centralized lineage queries and visualization services to provide a single graph-backed view of data flows.
Governance changes aligned data stewardship and BCBS 239 obligations by surfacing lineage for controls and reporting chains. The project improved transparency of data flows and accelerated root-cause analysis for data quality and reporting as stated in the implementation notes.
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Woodside Energy | Oil, Gas and Chemicals | 4718 | $8.6B | Australia | Neo4j | Neo4j Graph Data Platform | Database Management | 2019 | n/a |
In 2019, Woodside Energy implemented Neo4j Graph Data Platform as part of its Database Management strategy to support AI-led operations transformation. The deployment was executed within the Woodside Accelerator program, with internal Data Science, Artificial Intelligence, and Data Technology CDS teams in Perth driving architecture and ongoing operations.
The Neo4j Graph Data Platform was configured to host an AI knowledge graph, with the Artificial Intelligence team designing, implementing, and maintaining graph data models used by Woodside's Cognitive Advisor. Functional capabilities implemented included graph data modeling, knowledge graph storage and query workloads, and ETL ingestion pipelines specifically built to populate the graph data store.
Integrations were implemented between the Neo4j Graph Data Platform and Woodside's Cognitive Advisor, upstream staging in the AWS Data Lake, and downstream business intelligence workflows in Tableau, creating a directed data flow from lake to graph to analytics. Operational coverage spanned Data Science, AI, and Data Technology teams, and focused on use cases tied to operations transformation and enterprise AI project delivery.
Governance and operational processes emphasized model stewardship, maintenance and support of the graph environment, and training for Tableau users provided by the Data Technology team. Delivery responsibilities were held internally, with Data Science leading AI project orchestration into the Cognitive Advisor and the Data Technology CDS team maintaining ETL pipelines into the AWS Data Lake while supporting the Neo4j Graph Data Platform.
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Buyer Intent: Companies Evaluating Neo4j Graph Data Platform
- Comet Group, a Switzerland based Manufacturing organization with 1500 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
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