List of Amazon Relational Database Service (RDS) Customers
Amazon Web Services (AWS)
410 Terry Avenue North,
Seattle, 98109-5210, WA,
United States
Seattle, 98109-5210, WA,
United States
1 206-266-1000
Professional Services
135000
$128.7B
Since 2010, our global team of researchers has been studying Amazon Relational Database Service (RDS) 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 Relational Database Service (RDS) 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 Amazon Relational Database Service (RDS) for Database Management include: CVS Health, a United States based Healthcare organisation with 219000 employees and revenues of $372.81 billion, Cigna Healthcare, a United States based Insurance organisation with 71295 employees and revenues of $244.38 billion, Cardinal Health, a United States based Healthcare organisation with 53084 employees and revenues of $222.58 billion, General Motors, a United States based Automotive organisation with 162000 employees and revenues of $187.44 billion, Centene, a United States based Healthcare organisation with 60500 employees and revenues of $163.07 billion and many others.
Contact us if you need a completed and verified list of companies using Amazon Relational Database Service (RDS), 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 Relational Database Service (RDS) 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!
Apply Filters For Customers
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
|---|---|---|---|---|---|---|---|---|---|---|---|
 |
3M | Manufacturing | 61500 | $24.6B | United States | Amazon Web Services (AWS) | Amazon Relational Database Service (RDS) | Database Management | 2022 | n/a |
In 2022, 3M advanced its cloud platform by moving selected migrated workloads into Amazon Relational Database Service (Amazon RDS) as part of a broader AWS migration program. 3M migrated thousands of applications to Amazon Web Services using AWS Application Migration Service, and then advanced modernization by provisioning Amazon RDS for managed database services alongside AWS Lambda and Amazon EC2 compute.
The Amazon Relational Database Service (Amazon RDS) deployment focused on managed database operations, simplifying setup, patching, backup, and scaling for a diverse set of workloads. AWS Application Migration Service automated conversion of source servers to run natively on AWS, which reduced manual cutover work and enabled a phased transition of database workloads into Amazon RDS while serverless AWS Lambda functions were used to extend event driven processing and integration.
Operationally the implementation spanned multiple AWS Regions, bringing compute and database instances closer to customer endpoints and distributing resilience across regions. Integration points in this environment included Amazon EC2 for lift and shift compute, AWS Application Migration Service for automated server conversion, AWS Lambda for event processing, and Amazon RDS for managed database operations, creating a hybrid set of managed and self managed compute patterns.
Governance emphasized staged cutovers with minimal business downtime, region aware provisioning, and use of AWS native automation to standardize database provisioning and lifecycle operations. The move into Amazon Relational Database Service (Amazon RDS) supported 3M objectives for scalability, resilience, and faster modernization cycles as stated by the company during the rollout.
|
 |
ADP | Professional Services | 67000 | $21.8B | United States | Amazon Web Services (AWS) | Amazon Relational Database Service (RDS) | Database Management | 2020 | n/a |
In 2020, ADP implemented Amazon Relational Database Service (Amazon RDS) as a core persisted store for its next gen HCM SaaS on AWS, Category . The engagement was part of ADP’s broader adoption of AWS services guided by the AWS SaaS Factory program to accelerate a SaaS delivery model for human capital management and payroll.
ADP’s next gen HCM is built on a containerized microservice architecture running roughly 250 microservices on Amazon Elastic Kubernetes Service, with runtimes including Node.js, Go, and JVM. Amazon Relational Database Service (Amazon RDS) was used in both MySQL and PostgreSQL flavors to meet relational data-modeling needs alongside purpose-built stores, supporting requirements for latency, throughput, availability, elasticity, and data privacy.
The implementation integrated RDS with other AWS data services that handle secondary and specialized workloads, including Amazon DynamoDB for key value storage, Amazon Neptune for graph database support enabling dynamic teams, Amazon OpenSearch Service for free text search, and Amazon Kinesis for change data capture streaming from system of record databases to downstream data stores. This multi-service topology underpinned a multi-region approach recommended by AWS SaaS Factory to prepare the platform for global operational coverage and data residency constraints.
Organizationally, ADP combined new engineering hires with C-level sponsorship to establish centralized corporate and business unit support functions, and AWS SaaS Factory ran onsite workshops to articulate tradeoffs for multi-tenancy and data isolation strategies. ADP’s guidance emphasized evaluating multi-tenancy models for Amazon RDS and choosing the mix of managed services versus custom technology, while ensuring governance, compliance, and operational processes were defined to support the SaaS operating model.
|
 |
AllianceBernstein | Banking and Financial Services | 4380 | $4.5B | United States | Amazon Web Services (AWS) | Amazon Relational Database Service (RDS) | Database Management | 2019 | n/a |
In 2019, AllianceBernstein implemented Amazon Relational Database Service (RDS). The implementation aligned to the Apps Category and established Amazon Relational Database Service (RDS) as a core managed relational database layer for the firm, supporting cloud database operations and managed SQL workloads.
The deployment focused on standard RDS configuration patterns, including instance provisioning, parameter group and security group configuration, and use of IAM policy controls for access management. Implementation work referenced Managed SQL MI cloud database management practices and incorporated Delphix Engine for database virtualization, extending Delphix from onsite deployments into cloud-hosted RDS instances.
Integrations explicitly included AWS networking and security constructs such as VPC configuration, IAM policy and cross account access, S3 buckets for storage interfaces, and AWS Config and CloudTrail ingestion into Splunk for centralized monitoring and audit. The RDS implementation was executed within a hybrid cloud context alongside Azure and Snowflake operations, reflecting cross-cloud operational tooling and centralized observability.
Operational governance was driven by the database engineering team and Cloud Architect staff, with an emphasis on Cloud Information Security Framework controls, company-wide rollout of Delphix Database Virtualization, and a firm wide Data Catalog and governance program implemented using Alation. The work was positioned to standardize managed relational database practices across on-premises and public cloud platforms, and to formalize access, monitoring, and catalog governance for database assets.
|
 |
Altair Engineering | Professional Services | 3300 | $666M | United States | Amazon Web Services (AWS) | Amazon Relational Database Service (RDS) | Database Management | 2018 | n/a |
In 2018 Altair Engineering deployed Amazon Relational Database Service (RDS) to strengthen Database Management within its AWS cloud footprint. The implementation was executed alongside a broader AWS platform configuration that included VPC, EC2, S3, IAM, Elastic Load Balancing, Auto Scaling, CloudFront, Elastic Beanstalk and CloudWatch to support high availability and fault tolerance. Amazon Relational Database Service (RDS) instances were provisioned to support Development, QA, UAT and Production environments, and the scope centered on DevOps and engineering teams responsible for CI and CD pipelines and platform operations.
Configuration and functional modules implemented included creation and configuration of RDS database instances, security groups and IAM policies to control access to VPC resources, and use of AWS Database Migration Service to move datasets into RDS and S3. Serverless components were integrated, with AWS Lambda functions analyzing objects stored in S3 and CloudWatch used for monitoring logs and metric based alerting. Infrastructure as code was realized through Terraform modules, with Jenkins pipelines integrated with Terraform for continuous deployment, and configuration management automated using Ansible playbooks and roles to apply runtime configuration changes.
Container orchestration and runtime integration were addressed via AWS ECS and AWS EKS, with ECS tasks and services defined to host application components that access RDS. Source control and CI tooling included Git and GitHub repositories together with GitLab, Jenkins served as the continuous integration server with managed plugins, and ELK plus CloudWatch provided log aggregation and observability. Monitoring and server lifecycle automation leveraged Nagios and Zenoss APIs orchestrated through Ansible playbooks.
Governance emphasized identity and access management, creating IAM user accounts and group based permissions to restrict access to RDS and adjacent AWS resources, and applying network level security groups to control access to EC2 and RDS instances. Release and promotion processes spanned Development, QA, UAT and Production, with platform engineers supporting environment promotion and resolution of build failures. The record documents Altair Engineering use of Amazon Relational Database Service (RDS) in 2018 as a managed Database Management component embedded in a CI and CD oriented AWS infrastructure.
|
 |
AltaMed | Healthcare | 5700 | $1.8B | United States | Amazon Web Services (AWS) | Amazon Relational Database Service (RDS) | Database Management | 2021 | n/a |
In 2021 AltaMed implemented Amazon Relational Database Service (RDS) as a core Database Management capability within a broader AWS data ecosystem. The deployment was architected alongside Amazon S3 and EC2, with configurations explicitly designed to meet SOC2 and HIPAA requirements through encryption at rest and in transit, audit logging, and comprehensive recovery planning. The implementation was led by a Senior Manager of Data Services and supported by a five person DBA team focused on operational resilience and compliance.
Amazon Relational Database Service (RDS) was provisioned with production-grade instance sizing and performance tuning to support an enterprise data warehouse and downstream analytics. Teams developed and optimized Python based ETL and ELT pipelines to ingest data from diverse sources and to populate the warehouse, accompanied by automated backup and point in time recovery patterns and parameter management to stabilize query performance. The project emphasized data archiving and storage tiering to control active dataset size while preserving historical access for analytics and compliance.
Integrations centered on S3 for staging and long term archiving, S3 Glacier for compliance archival, and EC2 hosted compute for ETL workloads, with RDS serving as the managed relational store for transactional and analytical workloads. Operational coverage included Data Services and Analytics functions across the organization and extended to enterprise reporting, compliance reporting, and downstream analytical models. The architecture supported hardened audit trails and role based access controls to enforce data handling standards.
Governance was operationalized through formal code management and release processes using TFS and Git, automated testing frameworks, and mandatory peer code reviews prior to production deployment of ETL scripts and pipeline configurations. Staff development and training in SQL, Python, AWS, and data modeling were used to raise team capability, and reliability and recovery plans were documented and exercised as part of ongoing operations.
Explicit outcomes reported from the initiative included a 99% improvement in data processing times for ETL workloads, a 55% reduction in monthly AWS spend achieved through instance rightsizing, storage tiering and reserved or spot instance usage, a 70% reduction in production data volume via archival to S3 Glacier, an estimated 50% reduction in operational costs tied to archiving and optimization, and an 80% reduction in production issues following automated testing and peer review processes, while maintaining SOC2 and HIPAA compliance.
|
 |
|
Life Sciences | 28000 | $33.4B | United States | Amazon Web Services (AWS) | Amazon Relational Database Service (RDS) | Database Management | 2020 | n/a |
|
|
|
|
Life Sciences | 7500 | $3.2B | United States | Amazon Web Services (AWS) | Amazon Relational Database Service (RDS) | Database Management | 2018 | n/a |
|
|
|
|
Banking and Financial Services | 1989 | $1.2B | United States | Amazon Web Services (AWS) | Amazon Relational Database Service (RDS) | Database Management | 2020 | n/a |
|
|
|
|
Banking and Financial Services | 1000 | $250M | United States | Amazon Web Services (AWS) | Amazon Relational Database Service (RDS) | Database Management | 2020 | n/a |
|
|
|
|
Banking and Financial Services | 1500 | $920M | United States | Amazon Web Services (AWS) | Amazon Relational Database Service (RDS) | Database Management | 2019 | n/a |
|
Showing 1 to 10 of 72 entries
Buyer Intent: Companies Evaluating Amazon Relational Database Service (RDS)
ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating Amazon Relational Database Service (RDS). Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating Amazon Relational Database Service (RDS) for Database Management include:
- Hecht Kugellager, a Germany based Distribution organization with 28 Employees
- Loyola University Chicago, a United States based Education company with 4000 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated |
|---|---|---|---|---|---|---|
 |
Hecht Kugellager | Distribution | 28 | $8M | Germany | 2025-11-22 |
 |
Loyola University Chicago | Education | 4000 | $700M | United States | 2025-04-28 |
FAQ - APPS RUN THE WORLD Amazon Relational Database Service (RDS) Coverage
Amazon Relational Database Service (RDS) is a Database Management solution from Amazon Web Services (AWS).
Companies worldwide use Amazon Relational Database Service (RDS), from small firms to large enterprises across 21+ industries.
Organizations such as CVS Health, Cigna Healthcare, Cardinal Health, General Motors and Centene are recorded users of
Amazon Relational Database Service (RDS) for Database Management.
Companies using Amazon Relational Database Service (RDS) are most concentrated in Healthcare, Insurance and Automotive, with adoption spanning over 21 industries.
Companies using Amazon Relational Database Service (RDS) are most concentrated in United States, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Amazon Relational Database Service (RDS) across Americas, EMEA, and APAC.
Companies using Amazon Relational Database Service (RDS) range from small businesses with 0-100 employees - 4.17%, to mid-sized firms with 101-1,000 employees - 6.94%, large organizations with 1,001-10,000 employees - 20.83%, and global enterprises with 10,000+ employees - 68.06%.
Customers of Amazon Relational Database Service (RDS) 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 Amazon Relational Database Service (RDS) customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Database Management.