List of Vertica Analytics Platform Customers
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Since 2010, our global team of researchers has been studying Vertica Analytics 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 Vertica Analytics Platform for ML and Data Science Platforms 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 Vertica Analytics Platform for ML and Data Science Platforms include: UBS, a Switzerland based Banking and Financial Services organisation with 106789 employees and revenues of $57.05 billion, SiriusXM, a United States based Media organisation with 5680 employees and revenues of $8.95 billion, Square, a United States based Professional Services organisation with 12428 employees and revenues of $7.68 billion, Riot Games, a United States based Media organisation with 4200 employees and revenues of $1.50 billion, Rockstar Games, a United States based Professional Services organisation with 900 employees and revenues of $1.40 billion and many others.
Contact us if you need a completed and verified list of companies using Vertica Analytics 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 Machine Learning software purchases.
The Vertica Analytics 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 Machine Learning 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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LOCKON | Professional Services | 140 | $22M | Japan | Vertica | Vertica Analytics Platform | ML and Data Science Platforms | 2017 | n/a |
In 2017, LOCKON implemented Vertica Analytics Platform to power its new Audience EBiS service which measures and evaluates people’s exposure to marketing contents. LOCKON, a Japan-based market analysis company, launched Audience EBiS to capture event level marketing exposure and engagement data across client campaigns, with an implementation scoped for high volume and high velocity data processing.
Vertica Analytics Platform served as the core analytical engine within the ML and Data Science Platforms category, providing columnar storage, massively parallel processing and in platform SQL to support real time querying, sessionization and audience attribution workflows. The platform configuration emphasized high throughput ingestion and analytical pipelines to enable event level segmentation, cohort analysis and fast ad hoc exploration consistent with audience measurement use cases.
Operational coverage focused on LOCKON’s marketing analytics and product teams in Japan, where governance centered on data pipeline orchestration, analytical model lifecycle management and reporting workflows for the Audience EBiS service. The implementation enabled real time analysis of up to 10 billion pieces of data a year to support measurement and evaluation of exposure to marketing contents.
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Riot Games | Media | 4200 | $1.5B | United States | Vertica | Vertica Analytics Platform | ML and Data Science Platforms | 2012 | n/a |
In 2012, Riot Games implemented Vertica Analytics Platform to centralize analytics workloads for its data science and analytics teams, aligning with its ML and Data Science Platforms needs. The Vertica Analytics Platform was deployed to support high-volume game telemetry and player behavior analysis, providing a SQL-first environment for exploratory analytics and feature engineering.
The implementation leveraged a distributed, shared-nothing analytics cluster architecture, using columnar storage and a massively parallel processing query engine to optimize large-scale ad hoc queries and model training extracts. Functional capabilities emphasized in-database analytics and machine learning primitives, scalable query concurrency, and high-throughput ingestion to sustain continuous event and session data flows.
Operational coverage included data science, analytics, live game operations, and product analytics workflows, with the Vertica Analytics Platform used as the central analytical store for feature pipelines and model scoring feeds. Deployment and configuration focused on cluster sizing, storage tiers, and query resource governance to balance exploratory and production inference workloads.
Governance and workflow changes centered on centralized data catalogs, role-based access controls, and standardized SQL-based feature definitions to improve reproducibility of experiments and production model handoffs. The implementation placed emphasis on instrumentation of query patterns and schema design to support iterative feature development and operational analytics across Riot Games.
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Rockstar Games | Professional Services | 900 | $1.4B | United States | Vertica | Vertica Analytics Platform | ML and Data Science Platforms | 2002 | n/a |
In 2002, Rockstar Games implemented the Vertica Analytics Platform to centralize analytics and support advanced data science work across the studio. The Vertica Analytics Platform was adopted to address the companys ML and Data Science Platforms needs, leveraging high-performance columnar analytics, SQL-based feature engineering, and in-database machine learning capabilities that are typical for the category. Deployment targeted a mid-enterprise footprint appropriate for a 900-employee, 1.4 billion revenue developer, with infrastructure designed to ingest high-volume telemetry and batch data for iterative model development.
Implementation emphasis was on enabling data engineering and analytics teams to operationalize player behavior analysis, monetization analytics, and production reporting workflows on the Vertica Analytics Platform. Configuration aligned with category best practices, including centralized data ingestion, SQL analytics for feature creation, model training orchestration, and model scoring workflows to support continuous experimentation. Governance and operational controls focused on schema management, role based access controls for analytics users, and pipeline orchestration to align data science delivery with game development and live operations cycles.
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Media | 5680 | $9.0B | United States | Vertica | Vertica Analytics Platform | ML and Data Science Platforms | 2013 | n/a |
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Professional Services | 12428 | $7.7B | United States | Vertica | Vertica Analytics Platform | ML and Data Science Platforms | 2014 | n/a |
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Media | 2500 | $620M | United States | Vertica | Vertica Analytics Platform | ML and Data Science Platforms | 2011 | n/a |
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Banking and Financial Services | 106789 | $57.1B | Switzerland | Vertica | Vertica Analytics Platform | ML and Data Science Platforms | 2011 | n/a |
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Buyer Intent: Companies Evaluating Vertica Analytics Platform
- Assurances du Credit Mutuel, a France based Insurance organization with 3424 Employees
- Acquis Compliance, a India based Professional Services company with 50 Employees
- Luftansa Company, a United States based Banking and Financial Services organization with 20 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
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