Cloud repatriation is the process of migrating workloads, including databases, from public-cloud environments back to on-premises data centers, private clouds, or hybrid infrastructures. Organizations pursue repatriation to improve security, reduce costs, enhance performance, or meet data-sovereignty requirements.
Based on Foundry’s cloud computing study in 2024, 90% of IT decision makers have experienced some obstacles with their cloud adoption over the past 12 months, such as:
While the reasons for repatriation vary, for over 51% of the decision makers, the issues lie with security.
Security and control: Companies with stringent security needs prefer on-premises solutions, in order to minimize attack surfaces, enforce custom security policies, and ensure complete visibility into infrastructure vulnerabilities.
Performance optimization: In cloud environments, latency-sensitive applications, high-throughput analytics, and mission-critical database workloads may experience performance limitations. On-premises and private cloud solutions can offer more predictable performance with direct hardware optimizations.
Cost efficiency: Public cloud costs, including data egress fees, unpredictable pricing models, and long-term TCO considerations, often drive organizations to reassess their cloud strategies. By repatriating, businesses can reduce operational expenses and gain greater control over infrastructure costs.
Data governance and compliance: Regulatory frameworks, such as GDPR, HIPAA, and industry-specific mandates, often require strict data-residency and sovereignty measures. Repatriation ensures organizations maintain direct control over sensitive data.
Vendor lock-in concerns: Some organizations repatriate to avoid dependency on a single cloud provider, ensuring flexibility and avoiding excessive costs associated with proprietary cloud services.
Many businesses repatriate core database workloads while keeping some applications in the public cloud (SaaS), leveraging a hybrid architecture for optimal flexibility.
Organizations build private clouds using containerized or virtualized environments to replicate cloud benefits while retaining control.
Businesses invest in high-performance, on-premises infrastructure optimized for database workloads, often integrating advanced storage and compute solutions.
Cloud repatriation isn’t a one-size-fits-all solution. The best candidates for repatriation are high-cost, latency-sensitive, compliance-driven, or security-critical workloads, which benefit from better cost efficiency, performance, and data control when run on-premises, in private clouds, or hybrid environments.
Workload suitability: Not all workloads benefit from repatriation—identify which databases have high latency sensitivity, regulatory needs, security, or cost concerns.
Skill and resource availability: On-premises infrastructure requires in-house expertise. Assess whether your team has the necessary skills to manage database workloads effectively.
Migration complexity: Evaluate the complexity of moving large-scale database workloads and assess potential downtime, data consistency issues, and application dependencies.
Total cost of ownership (TCO) analysis: Ensure repatriation will lead to cost savings when factoring in infrastructure, staffing, and maintenance costs.
As organizations seek greater control over costs, performance, security, and data sovereignty, moving database workloads from SaaS environments to on-premises, private cloud, or hybrid architectures requires a strategic and well-executed approach. OpenText™ Analytics Database (Vertica) offers the tools, expertise, and flexibility needed to facilitate a seamless migration while optimizing performance and scalability.
Deploy OpenText Analytics Database on-premises, in private cloud, or in hybrid model without vendor lock-in. It supports bare metal, virtualized environments, Kubernetes, and containerized deployments, and integrates with leading cloud and on-premises storage solutions for optimized performance.
OpenText’s migration tools and services enable smooth transition from SaaS-only databases. ETL, batch processing, and real-time streaming support efficient data transfer. Parallel processing and data compression reduce migration time and storage costs.
Avoid unpredictable cloud costs, including compute, storage, and egress fees. Optimize licensing models for lower total cost of ownership (TCO). Support workload elasticity with hybrid and on-prem scaling options.
Leverage in-database machine learning to train and deploy models at scale for AI-driven insights.Ensure high-speed querying with columnar storage and MPP architecture. Run SQL queries directly on data stored in object storage (e.g., Amazon S3, HDFS, Azure Data Lake, Google Cloud Storage).
OpenText™ Professional Services assist with assessment, planning, and execution. Automated monitoring capabilities reduce operational burden. 24/7 enterprise-grade support for ongoing optimization and troubleshooting.
For organizations seeking cost-effective, high-performance data warehousing and analytics solution, OpenText Analytics Database (Vertica) offers a powerful alternative to public-cloud-only providers. Designed for advanced analytics, machine learning, and high-speed querying, OpenText delivers high data security, predictable performance, lower total cost of ownership (TCO), and full data sovereignty—without cloud egress fees or vendor lock-in. Whether deployed on-premises, in a private cloud, or in a hybrid architecture, our analytics database ensures maximum efficiency for mission-critical analytical workloads, enabling organizations to regain control over their infrastructure while optimizing costs and performance.
Analyze massive data sets with minimal compute and storage