The public cloud has redefined agility and scalability for data-driven businesses. But for many large enterprises, particularly in security- and compliance-intensive industries, the cloud’s promise is being weighed against the realities of data control, sovereignty, and risk.
Increasingly, organizations are repatriating analytical workloads—pulling them back from public cloud platforms and redeploying them in private, on-premise, or hybrid environments where they can enforce stricter governance. At the center of this shift? The analytical database—a foundational technology for strategic decision-making.
In a recent survey conducted by OpenText in partnership with Foundry, over 200 IT decision-makers from large enterprises globally were interviewed. Security and privacy concerns emerged as a leading driver for cloud repatriation. Among those who have already moved workloads back from the public cloud, 92% reported an improvement in their overall security posture.
This move doesn’t signal a retreat from digital transformation. Instead, it marks a deeper evolution: one where data architecture aligns with the enterprise’s risk appetite and regulatory obligations without compromising speed or insight.
Analytical databases: The intelligence core of the enterprise
Analytical databases are not just storage engines—they are the foundation for operational reporting, customer insights, forecasting, compliance audits, and even machine learning pipelines. They centralize massive, high-value data assets from across business units, geographies, and systems.
In large enterprises, the data flowing through these systems includes:
- Customer interactions, churn signals, and segmentation
- Product usage telemetry and performance analytics
- Board-level metrics, P&L summaries, and cash flow insights
- Sensitive operational benchmarks (e.g., SLAs, error rates, uptime)
This makes the analytical database both a mission-critical asset and a prime target for security threats and regulatory scrutiny.
Why Cloud is no longer the default for analytics
While cloud-native platforms offer ease of use and elasticity, they also abstract away control, making them ill-suited for some of the most sensitive analytics workloads in regulated environments. Here’s why large enterprises are rethinking the public cloud for analytical databases:
1. Data sovereignty and jurisdictional risk
Cloud vendors often replicate data across global infrastructure for redundancy and performance. However, this can inadvertently violate data residency laws or regulatory frameworks that require data to remain within a specific geographical area or under local jurisdiction.
For example, a financial institution operating in the EU must ensure compliance with GDPR, which mandates strict control over cross-border data transfers. Public cloud vendors may not guarantee data locality at the level required.
2. Security and forensics limitations
In public cloud-hosted analytics environments, enterprises have limited visibility into the underlying infrastructure. This hinders their ability to:
- Conduct a deep dive forensic analysis after an incident
- Validate security patch timelines
- Review full-fidelity access logs or system calls
This black-box limitation is a non-starter for organizations with dedicated Information Security teams or strict audit requirements.
3. Encryption and key management constraints
Many enterprises have existing HSM (Hardware Security Module) integrations or mandate the use of customer-managed encryption keys. Public cloud services may offer key management services, but they often lack the granularity or integration capabilities required by highly regulated industries.
4. Data movement and API exposure
Public cloud analytics architectures often depend on multi-stage ELT (extract-load-transform) pipelines, where data moves between storage layers, compute engines, and third-party services. This frequent movement:
- Expands the attack surface across APIs, data connectors, and integration points
- Breaks lineage visibility, making it harder to track data provenance for audits
- Introduces latency and risk, especially when sensitive datasets are staged or cached in intermediate formats
For large enterprises with strict governance mandates, this fragmented architecture creates a compliance liability and a performance penalty, especially when handling massive analytical workloads that must remain consistent, traceable, and secure.
Industry spotlights: Why cloud repatriation matters now
In industries with strict regulations and sensitive data, the risks of keeping everything in the public cloud are starting to outweigh the benefits. Here’s how repatriation is helping key sectors take back control.
Financial services
- Risks: Insider threats, regulatory audits, strict data localization (e.g., MAS, FCA)
- Use cases: Real-time risk modeling, fraud detection, customer churn analysis
- Why repatriate? Need for enforced governance, secure ML, and reduced risk in data pipelines involving sensitive financial data
Government
- Risks: National security classification, FOIA compliance, cyber warfare concerns
- Use cases: Citizen analytics, operational efficiency, budget allocation
- Why repatriate? Requires air-gapped deployment, full auditability, and absolute control over encryption keys
Healthcare
- Risks: HIPAA compliance, PHI/PII exposure, ransomware attacks
- Use cases: Patient outcome analytics, clinical trial optimization, predictive diagnostics
- Why repatriate? Need to keep PHI in secure environments with verifiable audit trails and controlled access
Telecom
- Risks: Network data exposure, competitive intelligence leaks, global regulatory patchwork
- Use cases: Network performance monitoring, churn analytics, capacity planning
- Why repatriate? Reduce latency and risk by processing analytics close to the source while maintaining compliance
Repatriation isn’t about going backward—it’s about taking control. For sectors that can’t afford security lapses or regulatory gaps, bringing analytics workloads back on-prem or into hybrid environments is simply the smarter move.
Planning for cloud repatriation: What enterprise leaders should consider
If your organization is considering repatriating analytical workloads, here are the key factors to evaluate:
- Risk profile of the data: Is the data subject to industry-specific regulation or legal scrutiny?
- Governance capabilities: Do you have adequate control over access, lineage, and key management in your current setup?
- Performance needs: Can you achieve the same or better performance by analyzing data closer to its source?
- Data gravity and integration: Are you constantly moving data into the cloud just to analyze it?
- Audit readiness: Can you deliver complete visibility and evidence to regulators and auditors when needed?
OpenText™ Analytics Database is designed to answer “yes” to all of these, with the added advantage of deployment flexibility to adapt as your data strategy evolves.
Repatriation with OpenText™ Analytics Database
To mitigate these risks while maintaining analytical performance, many enterprises are repatriating their analytical databases using OpenText Analytics Database.
Formerly known as Vertica, OpenText Analytics Database offers the full power of a high-performance SQL engine with unmatched flexibility to deploy in on-premises, private cloud, or hybrid environments.
Key Benefits:
- Security-first architecture: Encryption in motion and at rest, role-based access control, LDAP and Active Directory support, and comprehensive auditing.
- Flexible deployment: Deploy on virtual machines, bare metal, Kubernetes, or containers—in your data center, a sovereign private cloud, or a hybrid setup.
- High performance: Built for scale with columnar storage, aggressive compression, and parallel processing—delivering unmatchable speed without lock-in.
- AI/ML-ready: Supports in-database machine learning to reduce data movement and minimize risk.
Aligning data architecture with security mandates
As analytics becomes more central to enterprise success, the cost of getting it wrong grows exponentially. Repatriating analytical databases to enterprise-controlled environments isn’t just a tactical move—it’s a strategic realignment that ensures security, compliance, and performance stay under your control.
With OpenText Analytics Database, large enterprises no longer have to choose between agility and assurance. You can run high-performance analytics where it makes the most sense—in your data center, under your governance, with zero compromise on innovation.
Ready to take control of your analytical workloads?
See how OpenText Analytics Database can help your enterprise secure, scale, and simplify analytics—on your terms.
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Or speak with a solution expert today to discuss your repatriation strategy.
