List of AWS Database Migration Customers
Amazon Web Services (AWS)
410 Terry Avenue North,
Seattle, WA, 98109-5210,
United States
Seattle, WA, 98109-5210,
United States
1 206-266-1000
Professional Services
135000
$128.7B
Since 2010, our global team of researchers has been studying AWS Database Migration 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 AWS Database Migration for Data Migration 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 AWS Database Migration for Data Migration include: Nextera Energy, a United States based Utilities organisation with 16800 employees and revenues of $24.75 billion, Thomson Reuters, a Canada based Professional Services organisation with 26400 employees and revenues of $7.48 billion, Flagstar Bank, a United States based Banking and Financial Services organisation with 6993 employees and revenues of $2.58 billion, AJE Group, a Peru based Consumer Packaged Goods organisation with 15000 employees and revenues of $2.00 billion, Sallie Mae, a United States based Banking and Financial Services organisation with 1740 employees and revenues of $1.81 billion and many others.
Contact us if you need a completed and verified list of companies using AWS Database Migration, 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.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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AJE Group | Consumer Packaged Goods | 15000 | $2.0B | Peru | Amazon Web Services (AWS) | AWS Database Migration | Data Migration | 2019 | CloudHesive |
In 2019, AJE Group implemented AWS Database Migration as a central component of a corporate initiative to consolidate disparate on premises data assets and build a centralized analytics platform on Amazon Web Services, using Data Migration tooling to standardize ingestion across its 22 country footprint. The Data Migration program was executed with support from AWS partner CloudHesive and focused on moving SQL databases into a cloud native analytics architecture to improve data availability and cross‑functional access.
The implementation used AWS Database Migration Service to migrate on premises SQL databases into a cloud data architecture, Amazon S3 as the storage backbone for the data lake, AWS Glue to orchestrate and serverlessly manage ETL and discovery, and Amazon Redshift as the cloud data warehouse and universal repository. Amazon Redshift was configured to analyze structured and semi structured data across the data warehouse and data lake, and AWS Glue automated discovery and transformation tasks to accelerate ingestion and reduce extract transform load times by 35 percent.
Integration work centered on a data pipeline that fused AWS Database Migration Service replication with the S3 data lake and Glue job orchestration, feeding analytic models and the Amazon Redshift warehouse used by regional and country reporting. The deployment architecture emphasizes a centralized corporate data platform that consolidates metrics for commercial, sales, and customer-facing teams, enabling near real time availability of prior‑day information to operational users.
Governance and process changes accompanied the technical rollout, with the platform positioned as the single source of truth to support a data driven culture and to standardize data models across markets. Project governance involved centralizing access controls, cataloging via Glue discovery, and operationalizing Redshift as the canonical analytics store to reduce report fragmentation and improve cross‑team visibility.
Explicit outcomes reported from the implementation include a 35 percent reduction in ETL times, 15 percent savings in infrastructure costs from cloud consumption models, increased scalability to support expansion across countries, and faster access to data for internal teams, which improved data delivery timelines. With the core Data Migration and analytics platform in place, AJE Group is positioned to expand predictive analytics and AI use cases using the consolidated data lake and Redshift analytics layer.
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Altair Engineering | Professional Services | 3300 | $666M | United States | Amazon Web Services (AWS) | AWS Database Migration | Data Migration | 2018 | n/a |
In 2018, Altair Engineering implemented AWS Database Migration to support a targeted Data Migration initiative into Amazon-managed stores. The work was executed as part of an AWS-centric infrastructure program that spanned Development, QA, UAT and Production environments and was integrated into existing CI/CD pipelines.
The AWS Database Migration configuration focused on creating Amazon RDS instances and invoking AWS Database Migration Service to move datasets into S3 buckets, with AWS Lambda functions built to perform object-level analysis and Amazon CloudWatch used to surface analysis results. Infrastructure as code was used extensively, with Terraform modules written to provision highly available EC2 instances and AWS EKS clusters, and nested CloudFormation stacks implemented to standardize repeatable stacks. Continuous integration and delivery was orchestrated through Jenkins pipelines integrated with Terraform, Git-based source control, and Ansible playbooks for application configuration and deployment automation.
Integrations included core AWS services VPC, EC2, S3, RDS, IAM, Elastic Load Balancing, Auto Scaling, CloudFront, Elastic Beanstalk, ECS and EKS, while operational tooling leveraged ELK stack, Nagios and Zenoss monitoring. IAM governance was used to manage users and groups and to restrict permissions for CI processes, and security groups were applied to control access to EC2 and RDS resources. Container orchestration and deployment used AWS ECS task and service definitions and EKS clusters, with Ansible playbooks automating changes to task counts and service configuration.
Operational governance included modular Ansible roles and inventories for repeatable deployments, Terraform modules and custom plugins to extend provisioning behavior, and automated scaling policies based on CPU and memory. The implementation was embedded into the product release cycle with DevOps ownership for environment management and build failure resolution, ensuring AWS Database Migration operated as a coordinated component of Altair Engineering’s cloud platform.
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Availity | Professional Services | 1500 | $300M | United States | Amazon Web Services (AWS) | AWS Database Migration | Data Migration | 2022 | n/a |
In 2022, Availity implemented AWS Database Migration as a Data Migration initiative to accelerate cloud onboarding for its clearinghouse platform and related transactional systems. This implementation fed into a multi-year migration program that included a 2024 data center exit effort and culminated in a 2025 Experience Based Acceleration workshop to operationalize migration patterns at scale.
Implementation scope centered on migrating 13 critical workloads selected as templates for repeatable migrations, within a broader estate of more than 80 interconnected applications that support over 13 billion healthcare transactions annually. AWS Database Migration was used alongside Amazon Elastic Kubernetes Service, Amazon RDS, AWS Database Migration Service, and Amazon EC2 to address both data movement and containerized application hosting as part of a coordinated Data Migration strategy.
The deployment architecture established a customer VPC spanning three availability zones, with EC2 instances distributed per availability zone to maintain resilience and uptime. Container images were managed in Amazon Elastic Container Registry and migrations leveraged Direct Connect for secure network connectivity to AWS, while EKS operational improvements targeted automation through EKS Karpenter and Automode. These architectural components were validated during immersive, hands-on sessions to ensure operational readiness for production workloads.
Governance and rollout were driven by a three-day Experience Based Acceleration workshop that brought over 80 participants together for hands-on migration delivery and knowledge transfer. Senior sponsorship and rapid decision making were emphasized, AWS-led break-out sessions identified platform improvements, and cross-functional teams and program management coordinated cutover sequencing to minimize operational disruption while continuing product development activities.
Outcomes documented in the engagement include the migration of 13 critical applications during the intensive delivery, a 4.9 out of 5 Customer Satisfaction Score, achievement of over 40 EBA goals, and hands-on upskilling for more than 70 Availity engineers across 10 teams. The initiative produced 11 identified platform improvement opportunities and surfaced cost optimization recommendations, while creating repeatable migration patterns that position Availity to scale subsequent Data Migration efforts using AWS Database Migration and related AWS services.
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Flagstar Bank | Banking and Financial Services | 6993 | $2.6B | United States | Amazon Web Services (AWS) | AWS Database Migration | Data Migration | 2021 | n/a |
In 2021, Flagstar Bank deployed AWS Database Migration as a Data Migration initiative to support ETL pipelines, database consolidation, and downstream analytics workloads. The engagement was led by the bank’s data management organization and centered on operationalizing continuous change data capture and targeted migrations into cloud-hosted repositories.
The implementation integrated AWS Database Migration with existing Infosphere DataStage ETL designs and complementary AWS services, explicitly using AWS DMS services and Lambda functions to orchestrate extracts and transforms into Postgres targets. Workstreams included reusing CDC stored procedures for incremental loads, instrumenting S3 as a landing zone, and connecting to Snowflake with Snowpipe and Streams for datamart ingestion, while maintaining data movement to Salesforce and other application endpoints.
Operational scope covered enterprise data warehouse and datamart pipelines, supporting corporate banking functions such as mortgage servicing, mortgage origination, commercial loan origination and servicing, community banking deposit feeds, and AML data feeds to Actimize. The configuration approach preserved existing Infosphere DataStage jobs where appropriate, and extended automation to include shell scripting for lineage extraction and partial ETL automation, reflecting hands-on administration of DataStage and ongoing platform patching and version upgrades.
Governance elements implemented alongside AWS Database Migration included role based access control and data masking policies in Snowflake, and time travel queries for data recovery and auditing. The program emphasized collaboration across internal teams and external vendors to resolve performance and security issues, and retained explicit controls for CDC orchestration, access controls, and pipeline monitoring to align Data Migration activities with Flagstar Bank’s data management standards.
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Nextera Energy | Utilities | 16800 | $24.8B | United States | Amazon Web Services (AWS) | AWS Database Migration | Data Migration | 2018 | n/a |
In 2018 NextEra Energy implemented AWS Database Migration as part of a Data Migration initiative to centralize operational and application data into cloud analytics stores. The AWS Database Migration work focused on ingesting transactional and ticketing data into Amazon S3, loading analytics stores in Amazon Redshift, and provisioning Postgres targets for downstream reporting and application consumption.
The technical implementation relied on Talend for ETL orchestration, with jobs built to extract records via ServiceNow APIs and to pull CRM data using the tSalesforceInput component. Talend integrated layer jobs moved staged files from AWS S3 into Redshift and Postgres, Big Data Talend components such as tHiveInput, tImpalaLoad and Spark related components were used to populate Hadoop data lake zones, and Sqoop was used for HDFS to relational database transfers.
Explicit integrations documented in the implementation included Salesforce, ServiceNow, SAP HANA and BW HANA sources, Oracle extracts, Amazon Redshift, Postgres, Hadoop HDFS, and ActiveMQ for route and queue monitoring. Operational coverage included Florida Power and Light as the internal business unit client, BI consumers accessing Postgres views for Power BI dashboards and SSRS ad hoc reports, and OLAP cubes developed in SQL Server Analysis Services for multidimensional analytics.
Governance and operational controls were put in place through Talend Development Standards, repository driven source code migrations, metadata driven SSIS packages with package configuration for multi environment deployment, and Talend Management Console scheduling with cron triggers and Job Conductor orchestration. Process level coordination included regular Business IT requirement sessions, weekly status meetings, hosted calls with regional teams, and collaboration with a Data Mapping Team to validate source to target mapping rules and maintain deployment consistency.
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Professional Services | 150 | $25M | Netherlands | Amazon Web Services (AWS) | AWS Database Migration | Data Migration | 2018 | n/a |
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Banking and Financial Services | 1740 | $1.8B | United States | Amazon Web Services (AWS) | AWS Database Migration | Data Migration | 2020 | n/a |
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Healthcare | 7500 | $1.3B | United States | Amazon Web Services (AWS) | AWS Database Migration | Data Migration | 2020 | n/a |
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Professional Services | 26400 | $7.5B | Canada | Amazon Web Services (AWS) | AWS Database Migration | Data Migration | 2020 | n/a |
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Buyer Intent: Companies Evaluating AWS Database Migration
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FAQ - APPS RUN THE WORLD AWS Database Migration Coverage
AWS Database Migration is a Data Migration solution from Amazon Web Services (AWS).
Companies worldwide use AWS Database Migration, from small firms to large enterprises across 21+ industries.
Organizations such as Nextera Energy, Thomson Reuters, Flagstar Bank, AJE Group and Sallie Mae are recorded users of
AWS Database Migration for Data Migration.
Companies using AWS Database Migration are most concentrated in Utilities, Professional Services and Banking and Financial Services, with adoption spanning over 21 industries.
Companies using AWS Database Migration are most concentrated in United States, Canada and Peru, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of AWS Database Migration across Americas, EMEA, and APAC.
Companies using AWS Database Migration range from small businesses with 0-100 employees - 0%, to mid-sized firms with 101-1,000 employees - 11.11%, large organizations with 1,001-10,000 employees - 55.56%, and global enterprises with 10,000+ employees - 33.33%.
Customers of AWS Database Migration 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 AWS Database Migration customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Data Migration.