List of Teradata Appliance for Hadoop Customers
Teradata Corporation
17095 Via Del Campo,
San Diego, 92127, CA,
United States
San Diego, 92127, CA,
United States
1 866 548-8348
Professional Services
5700
$1.7B
Since 2010, our global team of researchers has been studying Teradata Appliance for Hadoop 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 Teradata Appliance for Hadoop for Data Warehouse Appliance 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 Teradata Appliance for Hadoop for Data Warehouse Appliance include: Walmart, a United States based Retail organisation with 2100000 employees and revenues of $681.00 billion, Apple, a United States based Manufacturing organisation with 166000 employees and revenues of $416.16 billion, CVS Health, a United States based Healthcare organisation with 219000 employees and revenues of $372.81 billion, ExxonMobil, a United States based Oil, Gas and Chemicals organisation with 61000 employees and revenues of $339.25 billion, Cardinal Health, a United States based Healthcare organisation with 53084 employees and revenues of $222.58 billion and many others.
Contact us if you need a completed and verified list of companies using Teradata Appliance for Hadoop, 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 Analytics and BI software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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3M | Manufacturing | 61500 | $24.6B | United States | Teradata | Teradata Appliance for Hadoop | Data Warehouse Appliance | 2012 | n/a |
In 2012, 3M implemented Teradata Appliance for Hadoop as a Data Warehouse Appliance to centralize high-volume analytics and enterprise reporting across manufacturing and corporate functions. The deployment positioned Teradata Appliance for Hadoop as an on-premise appliance layer integrated with the company Hadoop environment, providing a purpose-built MPP SQL processing tier for large scale analytic workloads and consolidated data storage.
The implementation emphasized standard Data Warehouse Appliance capabilities, including SQL-based analytics, scalable parallel query execution, bulk data ingestion and staging, and workload isolation for analytics processing. Operational scope targeted manufacturing analytics, supply chain reporting, and corporate business intelligence, with governance focused on centralized data models, ingestion workflows, access controls and role-based query governance to ensure consistent enterprise reporting and analytic consumption.
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Agilent Technologies | Life Sciences | 18000 | $6.5B | United States | Teradata | Teradata Appliance for Hadoop | Data Warehouse Appliance | 2017 | n/a |
In 2017, Agilent Technologies deployed Teradata Appliance for Hadoop as a Data Warehouse Appliance. The deployment established a consolidated analytical infrastructure intended to support enterprise reporting and research informatics across Agilent's Life Sciences operations. The initiative positioned the appliance as a central data repository for large scale analytic workloads and SQL based analytics.
Teradata Appliance for Hadoop was configured to provide scalable storage and SQL oriented analytic processing, leveraging the appliance's native Hadoop integration capabilities. Functional capabilities implemented included bulk data ingestion pipelines, columnar storage optimization, workload management and data partitioning to support complex analytical queries. The architecture emphasized appliance level orchestration with co located compute and storage to optimize throughput for analytic workloads.
Operational scope centered on enterprise analytics, business intelligence and research data workflows, with primary business functions impacted including analytics, reporting and research informatics. Governance and process changes focused on centralizing data access controls and establishing standardized SQL based analytic workflows, with IT and analytics teams assuming platform ownership. Source and further contact are noted as Contact ARTW.
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Amgen | Life Sciences | 28000 | $33.4B | United States | Teradata | Teradata Appliance for Hadoop | Data Warehouse Appliance | 2013 | n/a |
In 2013, Amgen implemented Teradata Appliance for Hadoop, deploying a Data Warehouse Appliance to consolidate high-volume analytical workloads. The Teradata Appliance for Hadoop was positioned to centralize enterprise-scale data processing and provide a unified analytics platform for structured and large-scale unstructured data.
The implementation emphasized appliance characteristics common to Data Warehouse Appliance deployments, including massively parallel processing compute nodes, integrated Hadoop storage sensitivity, distributed SQL access, and workload management for mixed batch and ad hoc queries. Configuration work focused on schema consolidation for enterprise data warehouse patterns, data ingestion pipelines into the Hadoop-enabled appliance, and optimization of analytic query patterns consistent with columnar and MPP architectures.
Operational coverage targeted cross-functional analytics, providing a platform for data science, business intelligence, and operational reporting across research, biomanufacturing, and commercial analytics domains. Access models and data provisioning workflows were aligned with departmental reporting needs, with shared storage and compute pools to support concurrent analytic workloads.
Governance and operational controls were established to support enterprise use, including role based access controls, data governance workflows, and orchestrated ingestion and refresh schedules. Teradata Appliance for Hadoop was documented as the central Data Warehouse Appliance for Amgen analytics, with implementation and ongoing stewardship coordinated through centralized data operations and analytics governance processes.
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Ancestry Operations | Professional Services | 1300 | $1.0B | United States | Teradata | Teradata Appliance for Hadoop | Data Warehouse Appliance | 2012 | n/a |
In 2012, Ancestry Operations implemented Teradata Appliance for Hadoop, a Data Warehouse Appliance, to establish a consolidated platform for large scale analytical processing across its genealogical and customer datasets. The deployment emphasized enterprise data warehousing and analytics use cases, aligning the Teradata Appliance for Hadoop with batch ETL and high concurrency query workloads used by Ancestry's data teams.
Configuration focused on appliance-level storage and parallel query processing, combined with Hadoop-native ingestion and schema-on-read patterns typical for this appliance category. The implementation encompassed data ingestion pipelines, centralized analytical storage, and support for advanced analytics workflows, with the Teradata Appliance for Hadoop serving as the primary analytic engine.
Integrations included Hadoop and NoSQL database technologies as part of the broader big data architecture, reflecting Think Big Analytics expertise in architecting Hadoop and NoSQL deployments for enterprise clients. Think Big Analytics is noted in the source context as a professional services firm that provided data science consulting and deployment assistance, and Teradata’s acquisition preserved Think Big’s operational independence to continue those services for clients such as Ancestry.
Governance and operational coverage centered on embedding data science consulting and architecture support into Ancestry’s existing analytics organization, with Think Big providing ongoing methodological guidance. The arrangement prioritized coordinated architecture ownership between Teradata appliance operations and Think Big’s Hadoop expertise, supporting Ancestry’s data engineering and analytics teams without altering the company’s stated deployment independence.
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Apple | Manufacturing | 166000 | $416.2B | United States | Teradata | Teradata Appliance for Hadoop | Data Warehouse Appliance | 2015 | n/a |
In 2015 Apple deployed Teradata Appliance for Hadoop as a Data Warehouse Appliance to establish a consolidated analytical platform for manufacturing and operations analytics. The deployment is described at the appliance level, with the Teradata Appliance for Hadoop positioned to deliver scale-out SQL analytics alongside Hadoop-native data access for large volume processing.
The implementation emphasizes appliance-class architecture and massively parallel processing, combining a SQL-oriented analytics engine with Hadoop integration to enable mixed workload processing. Functional capabilities implemented include high-performance SQL querying, workload management, data ingestion and ETL orchestration, and support for columnar storage and analytics workflows consistent with Data Warehouse Appliance architectures.
Integrations focus on the Hadoop ecosystem and enterprise analytical workloads, with the appliance acting as a central analytical store that consolidates Hadoop-resident datasets and serves manufacturing and operations reporting. Operational coverage centers on cross-functional analytics teams within manufacturing and related business functions, with the Teradata Appliance for Hadoop serving as the primary platform for joint SQL and Hadoop data access.
Governance was exercised through a centralized data platform model, role-based access controls, and standardized data modeling and ETL processes to support repeatable analytics delivery. Implementation activities included schema design, performance tuning of appliance nodes, and orchestration of data pipelines to align with enterprise analytics governance and operational workflows.
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Communications | 146040 | $122.4B | United States | Teradata | Teradata Appliance for Hadoop | Data Warehouse Appliance | 2013 | n/a |
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Banking and Financial Services | 213000 | $101.9B | United States | Teradata | Teradata Appliance for Hadoop | Data Warehouse Appliance | 2017 | n/a |
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Banking and Financial Services | 53597 | $25.2B | Canada | Teradata | Teradata Appliance for Hadoop | Data Warehouse Appliance | 2011 | n/a |
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Banking and Financial Services | 9261 | $2.8B | United States | Teradata | Teradata Appliance for Hadoop | Data Warehouse Appliance | 2017 | n/a |
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Banking and Financial Services | 93000 | $34.9B | United Kingdom | Teradata | Teradata Appliance for Hadoop | Data Warehouse Appliance | 2011 | n/a |
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Buyer Intent: Companies Evaluating Teradata Appliance for Hadoop
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| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
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FAQ - APPS RUN THE WORLD Teradata Appliance for Hadoop Coverage
Teradata Appliance for Hadoop is a Data Warehouse Appliance solution from Teradata.
Companies worldwide use Teradata Appliance for Hadoop, from small firms to large enterprises across 21+ industries.
Organizations such as Walmart, Apple, CVS Health, ExxonMobil and Cardinal Health are recorded users of
Teradata Appliance for Hadoop for Data Warehouse Appliance.
Companies using Teradata Appliance for Hadoop are most concentrated in Retail, Manufacturing and Healthcare, with adoption spanning over 21 industries.
Companies using Teradata Appliance for Hadoop are most concentrated in United States, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Teradata Appliance for Hadoop across Americas, EMEA, and APAC.
Companies using Teradata Appliance for Hadoop range from small businesses with 0-100 employees - 1.49%, to mid-sized firms with 101-1,000 employees - 4.48%, large organizations with 1,001-10,000 employees - 16.42%, and global enterprises with 10,000+ employees - 77.61%.
Customers of Teradata Appliance for Hadoop include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.
Contact APPS RUN THE WORLD to access the full verified Teradata Appliance for Hadoop customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Data Warehouse Appliance.