Top 10 Best Data Migration Services of 2026

Hexaware covers the migration lifecycle from advisory assessment and discovery through conversion, cloud deployment, testing, go-live, hyper-care, and ongoing support. Its documented work includes moving Cloudera data lakes to Azure Databricks, Oracle and Teradata warehouses to AWS and Snowflake, MySQL databases to Azure, SAS workloads to PySpark, and policy data between insurance administration platforms. Amaze® adds reusable automation for workload analysis, metadata extraction, code conversion, migration planning, and data validation, helping Hexaware handle large portfolios rather than isolated database moves.

The tradeoff is that Hexaware is designed for complex enterprise programs, so engagements typically involve substantial architecture, integration, testing, and client-side coordination rather than a lightweight self-service migration. It is particularly well suited to an insurer consolidating policy systems, a healthcare organization modernizing a regulated data lake, or a financial institution replacing legacy analytics infrastructure while preserving business logic.

Large ERP and CRM programs benefit from EY's integration work across SAP S/4HANA, Oracle, Microsoft Azure, Salesforce, and proprietary legacy applications. Teams can define schema mapping, transformation rules, validation controls, and rollback procedures while EY coordinates architecture, testing, security, and business readiness.

EY's delivery model suits multi-country programs needing migration wave planning, regulatory controls, and executive reporting. The tradeoff is heavier governance and consulting involvement than specialist migration software, which fits carve-outs, ERP modernization, and large merger integrations.

Infosys combines source assessment, data profiling, and schema mapping with cloud architecture, integration engineering, testing, and operational handover. Infosys Cobalt adds reusable automation assets, migration factories, and hyperscaler-specific patterns for AWS, Azure, Google Cloud, SAP, and Oracle estates. That structure supports migration wave planning across distributed business units and environments.

The tradeoff is coordination overhead because global teams, cloud partners, and client owners must align on sequencing and accountability. Infosys fits a multinational manufacturer consolidating regional ERP systems while retaining controlled validation and operational handover.

PwC differentiates its data migration work through industry-led delivery that connects technical movement with operating-model redesign and regulatory control. Teams assess source estates, apply data profiling, and coordinate transformation across ERP, CRM, cloud, and analytics environments.

Schema mapping and cutover planning support controlled movement between legacy and target systems. PwC is strongest for large programs requiring executive governance, cross-functional coordination, and post-migration ownership, but its delivery model is heavier than focused technical engagements.

Accenture migrates enterprise data across legacy, cloud, and packaged systems through migration factories and industry-specific delivery teams. Programs commonly cover data profiling, schema mapping, and reconciliation controls alongside application modernization and cloud architecture. myNav adds automated cloud assessment and landing-zone planning, while Accenture teams coordinate testing, deployment, and post-migration operations.

Deloitte differentiates its data migration work through consulting-led transformation programs that combine source-system assessment, cloud architecture, and operating-model redesign. Delivery teams cover schema mapping, integration dependencies, data quality controls, and controlled release sequencing across ERP, CRM, analytics, and core banking estates.

API architecture, governance, testing coordination, and post-migration support extend the work beyond isolated file movement. The approach suits regulated or multinational programs, but smaller migrations may receive more consulting overhead than needed.

IBM differs from narrower migration vendors by combining consulting-led programs with DataStage, Cloud Pak for Data, and Aspera transfer technology. DataStage handles parallel ETL workloads across relational, mainframe, cloud, and file-based systems.

InfoSphere Data Replication supports CDC for incremental movement, while Aspera addresses large-file transfers over high-latency networks. The portfolio offers broad governance and deployment flexibility, but delivery depends on specialist expertise and careful product selection.

Capgemini combines a Data Migration Factory delivery model with consulting for ERP, application, and cloud estate transitions. Its teams cover source assessment, ETL design, data cleansing, reconciliation, and cutover planning across SAP and non-SAP environments. The service suits complex programs that need architecture governance and managed execution, but smaller migrations may receive more process than they require.

Cognizant migrates legacy application and warehouse data into cloud estates through a consulting-led data modernization practice. Its Data Modernization Factory combines reusable migration accelerators with industry-specific engineering teams.

Delivery covers schema mapping, data profiling, transformation, validation, and cutover planning across large programs. API and automation depth depends on the selected cloud architecture and project team rather than a single public migration product.

KPMG suits regulated enterprises moving finance-heavy workloads where governance and implementation coordination matter more than self-service tooling. KPMG combines source-system assessment, data transformation, cloud migration, and application modernization across SAP, Oracle, Microsoft, AWS, and Azure environments. Its delivery model connects migration wave planning with controls for data quality, security, and operating-model change, but public service material gives less product-level detail about reusable APIs and automation than specialist migration vendors.