A 2026 buying guide to enterprise-grade data encryption solutions. Compare coverage, key management, performance, and compliance across 9 vendors.
This guide compares the leading data encryption solutions against the realities that support modern enterprise rollouts: data coverage, classification, encryption standards, centralized key management; policy enforcement; performance, and compliance.
The goal of this guide is to equip the enterprise-buyer seeking a data encryption solution that protects data at rest, in transit, and in use ⸺ without breaking workflows or driving up costs.
Below, each data encryption solution is scored on what matters in production: i.e. whether it can encrypt data wherever it resides; if key management scales effectively; and how it reduces risk while helping achieve compliance without hindering operations.
DataStealth employs an inline, field-level architecture that enables organizations to protect data as it flows in databases, APIs, file shares, and event streams, without requiring code changes or database schema rewrites.
It’s deployed as a scalable mesh composed of brokers and workers that intercepts traffic between applications and storage systems, inspects the payload in real-time, and applies data encryption before any sensitive data is written to disk or cloud services.
By sitting directly in the data path, DataStealth protects the data before it ever reaches logs, backups, or analytics layers; a key distinction from at-rest-only encryption tools.
DataStealth’s data coverage spans SQL/NoSQL databases; REST and GraphQL APIs; CIFS/NFS/S3 file stores, as well as streaming platforms like Kafka.
For older systems, DataStealth rewrites SQL queries and responses on the wire, so applications continue operating without recognizing that fields have been tokenized.
In streaming or ETL environments, the platform protects data in motion and ensures consumers downstream only receive the level of detail permitted by policy.
Discovery and classification are performed in real-time using data handlers that analyze payloads for patterns such as PCI, PHI, or PII.
These patterns trigger enforcement logic based not only on field type, but also on contextual signals such as identity, device posture, and regional data residency.
This context-aware protection allows organizations to enforce different access rules for the same fields depending on who is accessing the data, from where it is being accessed, and for what purpose it is.
Supports format-preserving encryption (FPE), strong cryptography, and TLS 1.2+ and mTLS. However, for assured data protection, DataStealth prioritizes tokenization to keep data at rest non-sensitive.
Tokenization removes sensitive data from storage entirely, neutralizing breach risk without relying on key secrecy. However, where cryptography is required, DataStealth utilizes strong, format-preserving encryption and enforces TLS 1.2+ or mTLS across all data flows.
Instead of relying on legacy KMS workflows, DataStealth uses a policy-as-code model where every data protection rule, along with its approvals, versions, and rollback options, is managed through a declarative, Git-friendly pipeline.
This model eliminates the need for teams to manage individual encryption keys, while still supporting integrations with HSMs or cloud KMS systems when cryptographic keys are needed.
Policies are granular and conditional: DataStealth can redact, mask, tokenize, or reveal data based on the requester, the request purpose, the user’s region, or the device’s risk profile.
Partial reveals (for example, only showing the last four digits of a credit card number) are also supported, allowing analytics and customer service functions to operate without full access to sensitive records.
Performance is maintained through horizontal scaling of brokers and workers, ensuring that throughput increases linearly with demand. Hot paths are optimized through deterministic token maps, eliminating the need for repeated cryptographic operations.
Since DataStealth operates without agent installations or application rewrites, both legacy and modern systems benefit from protection, with minimal deployment friction.
Every transformation, reveal, or denial event is logged in real-time and exportable to SIEM platforms, supporting compliance programs for PCI DSS, HIPAA, GDPR, and regional data residency requirements. Organizations can enforce policies, such as “data may not be stored in cleartext outside the EU,” without relying solely on developer discipline or firewall controls.
DataStealth is best suited for hybrid and multi-cloud organizations that require consistent data protection across diverse systems, particularly when field-level control, deterministic analytics, or zero-trust enforcement are top priorities. Adoption usually begins with a targeted pilot (such as tokenizing PCI data in a payments API) before scaling to broader workloads.
Thales CipherTrust offers a unified, multi-layered data protection platform designed to secure data across at-rest, in-transit, and in-use states in hybrid and multi-cloud environments.
It supports encryption at the file system, database, container, and application levels and includes connectors for major cloud platforms such as AWS, Azure, and Google Cloud.
The platform’s architecture provides enterprises with a single control plane to apply encryption, tokenization, and access controls across distributed environments.
CipherTrust integrates data discovery and classification capabilities that identify sensitive information across structured, and unstructured repositories.
These findings automatically trigger predefined security policies that ensure data such as PCI, PHI, and PII are protected according to organizational, and compliance requirements.
Risk visualizations enable security teams to prioritize areas that require encryption or ongoing monitoring.
This solution supports industry-standard algorithms, including AES, RSA, and FPE; and maintains certifications under FIPS 140-2, and the Common Criteria.
Enterprises that require the highest assurance can integrate the CipherTrust Manager with Thales Luna HSMs for secure key storage under FIPS 140-2 Level 3 conditions.
CipherTrust’s centralized key management model enables lifecycle control over encryption keys: including generation, rotation, revocation, and destruction, across multiple systems, and clouds.
The platform supports Bring Your Own Key (BYOK), and integrates with third-party KMS systems through KMIP. Access is governed using RBAC and MFA, ensuring only authorized personnel with an operational need can handle sensitive cryptographic material.
Granular RBAC, MFA, and least-privilege; AD/LDAP integration.
Policy enforcement is administered through fine-grained controls that define what data can be accessed, by whom, and under what circumstances.
These controls are tightly integrated with LDAP and Active Directory, allowing for consistent enforcement across all enterprise systems. Policies can limit privileged user access so that even system administrators cannot access decrypted data unless explicitly permitted.
Audit and compliance reporting are native features of the solution.
All encryption, key, and access operations are logged and can be streamed to SIEM platforms such as Splunk, QRadar, and ArcSight. Predefined dashboards support regulatory standards like GDPR, HIPAA, and PCI DSS.
Vormetric provides transparent database, and file encryption that protects data in on-premise, virtual, and cloud environments, without requiring application modifications.
Sensitive information is encrypted at the file system and volume levels using agents installed on target systems, ensuring protection across structured (e.g. Oracle, SQL Server), and unstructured (e.g. file shares) data sets.
The platform integrates with Thales' larger ecosystem for data discovery and classification, enabling automatic application of encryption policies based on predefined tagging and detection rules.
Vormetric supports a variety of strong encryption algorithms, including AES, 3DES, and ARIA, and offers cascaded cipher combinations for organizations requiring enhanced resistance to cryptographic attacks.
Key management is centralized through the Vormetric Data Security Manager (DSM), which is available as a virtual appliance or certified hardware appliance ⸺ up to FIPS 140-2 Level 3.
Policy enforcement is administered at granular levels, with access controls based on identity, process, time, file type, and privilege level.
Performance is optimized by running encryption at the server rather than through proxy systems, eliminating common bottlenecks.
Compliance and monitoring are supported through granular audit logs that track both successful and denied access events.
Azure Information Protection (AIP) is a cloud-native, label-based data protection system tightly integrated with Microsoft 365 services and Azure workloads.
Organizations use AIP to classify, label, and encrypt documents and emails in Exchange, SharePoint, OneDrive, and Teams.
For structured data, Azure SQL offers Transparent Data Encryption (TDE) for at-rest encryption, and Always Encrypted for client-side column-level protection.
AIP supports automatic and user-driven data classification based on preconfigured rules such as content type, destination, or file extension. Sensitivity labels determine permissions ⸺ such as view, edit, forward, or print ⸺ and persist with the document even after it is shared externally.
The platform uses RSA 2048-bit keys for asymmetric encryption, and AES for symmetric encryption within Azure SQL workloads.
All cryptography is FIPS-validated, however, control over key storage depends on the configuration. By default, Microsoft manages the keys, but enterprises can enable Customer-Managed Keys (CMK) via Azure Key Vault.
Key management is centralized in Azure Key Vault, where customers can control key lifecycle processes, including creation, rotation, deletion, and enforcement of access policies.
AIP’s Rights Management Service (RMS) handles encryption for most Office documents, though this approach is less flexible for enterprises that need strict separation of key custody from the cloud provider.
Policy enforcement is identity-based, ensuring that only authorized users can view or interact with protected content.
AIP’s performance benefits from Azure’s global infrastructure, which handles encryption and decryption, without adding noticeable latency in most enterprise workflows.
However, organizations adopting multi-cloud strategies may encounter friction if they need consistent encryption enforcement across Azure and non-Microsoft platforms.
Compliance visibility is achieved through Azure Monitor and exportable audit logs that track classification, access, and protection events. AIP helps organizations align with GDPR, HIPAA, and other regulatory requirements; however, limitations apply to organizations with strict key custody policies.
IBM Guardium Data Encryption delivers transparent encryption for databases, files, and backups across on-premise, cloud, and mainframe environments.
Guardium’s coverage spans major database platforms, including Oracle, SQL Server, DB2, MongoDB, and PostgreSQL, as well as backup archives and file systems.
Encryption occurs at the operating system or database storage level, meaning that database users and applications interact with data as normal, while the data on disk remains unreadable without the decryption keys.
Data classification is handled through IBM’s broader security suite, allowing administrators the ability to apply encryption policies based on system paths, database types, or file extensions.
IBM uses FIPS-validated symmetric encryption algorithms, ensuring compliance with government and industry security standards.
Guardium now integrates with Thales CipherTrust Manager for centralized key lifecycle management; aligning with best practices in modern key management, and eliminating the need for administrators to manage separate encryption systems.
Policy enforcement occurs at the database/file layer, and enables transparent access to data while maintaining strong segregation of duties.
Guardium is designed for enterprise-scale deployments, supporting hundreds of databases and large storage repositories, with minimal performance degradation.
Compliance and reporting are supported through detailed audit logs, which can be exported to SIEM systems. With native support for PCI DSS, HIPAA, GDPR, and similar frameworks, Guardium is well-positioned for organizations with regular audit cycles or regulated workloads, particularly in industries such as financial services or healthcare.
PKWARE delivers a platform focused on protecting structured and unstructured data, with specialized capabilities for encrypting databases, files, and email communications.
One of its core strengths lies in column-level encryption for relational databases, enabling organizations to selectively protect specific sensitive fields (such as credit card numbers or health identifiers) without compromising entire tables or impacting application performance.
The platform includes data discovery capabilities that scan file systems and database repositories to locate sensitive data before applying encryption or masking policies.
This targeted approach enables organizations to reduce risk without introducing universal encryption overhead.
PKWARE supports strong encryption standards, primarily using AES across both, file, and column-level implementations. For legacy environments, especially those running on IBM Z or IBM i mainframes, PKWARE integrates with built-in hardware cryptography to provide efficient encryption for aging systems.
Key management is handled through PKWARE’s central administration console, which supports lifecycle controls, access governance, and integrations with existing key management services.
Policies specify how data is protected, which users can access it, and under what conditions.
PKWARE automates enforcement wherever possible, meaning that once secure processing rules are defined, administrators do not need to manually encrypt datasets or track individual access requests.
PKWARE is typically used in environments requiring rapid rollout with minimal operational friction. The platform is compatible with hybrid infrastructures and allows encryption to be deployed at endpoints, servers, and cloud platforms with minimal configuration.
Compliance alignment is supported through audit logging and discovery-driven protection that meets standards like GDPR, HIPAA, and PCI DSS.
Begin with identifying your databases (SQL/NoSQL), file and object stores, SaaS apps, APIs, and streaming pipelines.
Note data formats ⸺ structured, semi-structured, unstructured ⸺ and latency constraints. If your workflows are API- or event-driven, you’ll benefit from inline controls that protect data before persistence.
Align requirements to compliance and key management. If auditors expect FIPS validation, HSM roots of trust, and rotation evidence, shortlist platforms with centralized key management and clean SIEM exports.
If your priority is reducing breach blast radius, and keeping data at rest non-sensitive, look to solutions that make tokenization the default, and reserve cryptography for what truly needs encryption.
Transparent, storage-layer encryption minimizes changes for legacy apps, but it does not restrict what downstream systems can read once they are inside the trust boundary.
Field-level, policy-driven protection enables you to redact, mask, or partially reveal data on-read, making it useful for analytics, support, and least-privilege access.
If you run a hybrid or multi-cloud environment, aim for a single control plane that enforces consistent policy across clouds and data planes.
If your teams ship services weekly, prefer policy-as-code so that security controls move at the speed of CI/CD ⸺ versioning, approvals, rollback ⸺ instead of relying on per-app libraries, and per-team key wiring.
Start with a narrow but noisy pathway – e.g. cardholder data in a payments API or PHI in an intake form – then measure: p95/p99 latency, join fidelity with deterministic tokens, and audit completeness. Expand only after you can prove that data remains protected in transit and at rest, and that, reveals are policy-gated and logged.
The pragmatic outcome for most enterprise data estates is to pair transparent at-rest encryption where necessary, and add inline, field-level controls where feasible. This keeps analytics fast, proves governance, and steadily starves breaches of useful plaintext.
Bilal is the Content Strategist at DataStealth. He's a recognized defence and security analyst who's researching the growing importance of cybersecurity and data protection in enterprise-sized organizations.
