List of Amazon Data Lake Storage Customers
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Since 2010, our global team of researchers has been studying Amazon Data Lake Storage 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 Amazon Data Lake Storage for Cloud Storage 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 Amazon Data Lake Storage for Cloud Storage include: GE HealthCare, a United States based Healthcare organisation with 53000 employees and revenues of $19.60 billion, Invista, a United States based Manufacturing organisation with 6000 employees and revenues of $1.50 billion, Pomelo Argentina, a Argentina based Banking and Financial Services organisation with 300 employees and revenues of $15.0 million and many others.
Contact us if you need a completed and verified list of companies using Amazon Data Lake Storage, 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 Amazon Data Lake Storage 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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GE HealthCare | Healthcare | 53000 | $19.6B | United States | Amazon Web Services (AWS) | Amazon Data Lake Storage | Cloud Storage | 2018 | n/a |
In 2018 GE HealthCare implemented Amazon Data Lake Storage as the data lake foundation for its GE Health Cloud on Amazon Web Services. The deployment used Amazon S3 as the cornerstone for storing near petabyte medical imaging datasets to enable sharing, visualization, and machine learning across care teams in the United States. The Amazon Data Lake Storage implementation centralized object storage for DICOM and derived imaging artifacts and supported analytics pipelines and collaboration workflows.
Architecture centered on an S3 backed data lake with lifecycle management, metadata indexing, and role based access control to support imaging collaboration and analytics workflows and to provide persistent training datasets for machine learning. Operational scope covered imaging departments and cross functional care teams in the United States, enabling image sharing and analytics to improve diagnoses and patient outcomes as described in the AWS case study. Governance emphasized centralized storage policies, access controls, and data retention controls to manage near petabyte datasets and to standardize operational workflows for imaging and analytics.
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Invista | Manufacturing | 6000 | $1.5B | United States | Amazon Web Services (AWS) | Amazon Data Lake Storage | Cloud Storage | 2020 | n/a |
In 2020 INVISTA implemented Amazon Data Lake Storage to build an enterprise data lake on AWS. The implementation used Amazon S3 as the storage layer with AWS Lake Formation, AWS Glue, and other AWS services to consolidate siloed plant data across manufacturing operations.
The deployment established a centralized data catalog along with ingestion and ETL pipelines using AWS Lake Formation and AWS Glue, enabling standardized metadata management, automated schema discovery, and role based access controls for analytics and machine learning. Amazon Data Lake Storage was configured to support data preparation and feature engineering workflows that feed ML driven analytics for predictive maintenance and operational performance monitoring.
Integrations concentrated on plant data sources and manufacturing operations data feeds to make curated datasets available to data scientists and analytics teams. Governance was operationalized through Lake Formation cataloging and access controls, and per the AWS case study the Lake Formation based data lake reduced time to insight for data scientists and contributed to operational savings and improved predictive maintenance outcomes.
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Pomelo Argentina | Banking and Financial Services | 300 | $15M | Argentina | Amazon Web Services (AWS) | Amazon Data Lake Storage | Cloud Storage | 2022 | n/a |
In 2022, Pomelo Argentina deployed Amazon Data Lake Storage on Amazon S3 to support its fintech card and payments platform across Latin America. The Amazon Data Lake Storage implementation centralized raw and curated payments data into S3 and used native AWS features to manage access, compliance, encryption and scalable analytics, aligning with the Apps Category .
The implementation configured S3 storage tiers, encryption at rest, identity and access management controls, and lifecycle policies to govern data retention and cost profiles, while exposing data for analytics and operations workflows in payments. Operational scope covered payments operations across Pomelo’s Latin America footprint and supported analytics for fraud detection, reconciliation and reporting, with governance focused on access controls and compliance monitoring. The move to S3 helped Pomelo optimize storage and encryption costs according to AWS optimizations and improved its analytics capabilities for payments operations in the region.
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