Cloud Database Security Market by Database Type (Non-Relational, Relational), Security Service (Access Control, Backup And Recovery, Compliance And Auditing), End User, Deployment Model, Organization Size - Global Forecast 2025-2032
Description
The Cloud Database Security Market was valued at USD 37.32 billion in 2024 and is projected to grow to USD 39.12 billion in 2025, with a CAGR of 5.51%, reaching USD 57.34 billion by 2032.
Framing the strategic imperative for cloud database security by synthesizing migration dynamics, threat evolution, regulatory pressures, and operational resilience requirements
Cloud database security sits at the intersection of modern data strategy and relentless threat activity, shaping how organizations protect critical assets while pursuing digital transformation. The rapid adoption of cloud-native architectures, containerized platforms, and distributed data stores has reshaped the perimeter and increased the attack surface, requiring security teams to rethink legacy controls and embed protection directly into data lifecycles. This introduction distills the drivers, constraints, and operational imperatives that should inform board-level discussions and security investment decisions.
As enterprises migrate diverse database workloads to cloud, they face a complex set of trade-offs between scalability, performance, and control. Data residency and compliance expectations layer additional obligations on architecture and procurement choices. Meanwhile, threat actors increasingly target database endpoints for high-value exfiltration and ransomware staging, emphasizing the need for observability, least-privilege access models, and resilient recovery capabilities. Taken together, these forces underscore why cloud database security must transition from a tactical checklist to a strategic competency embedded across engineering, operations, and risk management.
Identifying the primary transformative shifts redefining cloud database security including identity-first controls, diverse data models, DevSecOps integration, and supply chain constraints
The landscape of cloud database security is undergoing several transformative shifts that alter both risk profiles and defensive responsibilities. First, control planes and orchestration layers have become as valuable a target as the data stores themselves; attackers exploit misconfigurations and weak identity management at scale, prompting a shift toward identity-first security and continuous configuration validation. Organizations must therefore prioritize inventory accuracy and real-time posture assessment as foundational capabilities.
Second, the proliferation of non-relational database technologies, event-driven architectures, and multi-model stores has created diverse telemetry and protection requirements. Security architectures can no longer assume uniform APIs or access patterns; defenders must instrument bespoke controls and threat detection for document, graph, key-value, wide-column, and traditional relational engines. Third, the convergence of DevOps and security practices has elevated the importance of shift-left controls and automated policy enforcement within CI/CD pipelines. Finally, supply chain considerations and geopolitical dynamics are introducing new constraints on vendor sourcing and hardware procurement, requiring security and procurement teams to coordinate closely to preserve both performance and assurance.
Analyzing how United States tariff measures in 2025 are reshaping procurement economics, vendor delivery models, and architectural choices across cloud database security
The cumulative impact of recently announced tariffs and trade policy adjustments in the United States for 2025 has introduced material effects across the cloud database security ecosystem, influencing hardware procurement, vendor economics, and operational planning. Higher duties on select hardware components and networking gear increase total cost of ownership for on-premises and hybrid deployments, making public cloud services comparatively attractive while simultaneously pressuring cloud providers to optimize supply chains and component sourcing. This dynamic encourages greater scrutiny of where and how database workloads run and underscores the value of cloud-native security services that reduce dependency on custom hardware stacks.
In addition, tariffs affect the economics of appliance-based security solutions and specialized database protection appliances, prompting vendors to adapt their delivery models toward software-centric, subscription-driven offerings and managed services. Risk and compliance teams are responding by reassessing contractual clauses, SLAs, and vendor continuity plans to account for potential supplier disruptions and longer lead times. The net effect is an acceleration of architectural decisions that favor elasticity, portability, and software-defined security controls, while increasing the importance of vendor diversification and rigorous third-party risk management.
Delivering actionable segmentation insights across database types, organizational scale, deployment models, security services, and industry vertical constraints informing tailored security postures
Granular segmentation provides clarity on how security needs diverge across database types, organizational scale, deployment patterns, security services, and end-user industries. Security posture and required tooling vary significantly based on whether workloads run on non-relational stores versus relational engines; non-relational environments introduce distinct telemetry and access patterns across document, graph, key-value, and wide-column formats, while relational environments require tailored controls for engines such as MySQL, Oracle, PostgreSQL, and SQL Server. This technological heterogeneity requires security strategies that combine generic hardening practices with engine-specific threat detection and policy sets.
Organization size further differentiates capability needs and procurement models: large enterprises often demand integrated governance, advanced forensics, and vendor-managed services, whereas small and medium-sized enterprises frequently prefer turnkey solutions that reduce operational overhead and simplify compliance. Deployment model choices-hybrid cloud, private cloud, and public cloud-shape where responsibility for security lies and what controls are feasible; hybrid models emphasize consistent policy enforcement across on-prem and cloud, private clouds prioritize control and isolation, and public clouds shift more responsibility to managed service offerings and provider-native tools. The security service taxonomy-access control, backup and recovery, compliance and auditing, data encryption, database firewall, and threat detection-maps directly to risk scenarios and maturity levels, enabling organizations to prioritize investments against their highest exposures. Finally, end-user industries such as BFSI, government and defense, healthcare, IT and telecom, and retail and e-commerce present distinct regulatory, data privacy, and availability constraints, which should drive sector-specific control frameworks and incident response playbooks.
Explaining regional variations in cloud database security priorities and how regulatory, provider, and geopolitical forces shape protective architectures across global markets
Regional dynamics influence threat landscapes, regulatory regimes, and vendor ecosystems, producing divergent priorities and approaches to cloud database security. In the Americas, regulatory emphasis on data protection and evolving breach notification laws coexist with a competitive cloud provider market and a vibrant ecosystem of security startups, which together encourage rapid adoption of advanced monitoring, encryption, and managed detection capabilities. Organizations in this region frequently prioritize integration with existing compliance regimes and value practical, operational controls that enable rapid incident containment and forensic analysis.
In Europe, the Middle East & Africa, heightened regulatory scrutiny around data privacy and cross-border transfers compels organizations to emphasize data residency, encryption, and rigorous access governance, while regional fragmentation in legal frameworks necessitates adaptable, policy-driven security solutions. The Asia-Pacific region presents a complex mix of high-growth cloud adoption and substantial domestic cloud provider footprints; regional variations in regulatory expectations and infrastructure resilience demand flexible architectures that can deliver both performance and compliance. Across all regions, geopolitical considerations, local supply chain dynamics, and talent availability shape the selection and deployment of security controls and managed service relationships.
Profiling how vendors and service providers are differentiating through integration depth, managed services, analytics, and automation to solve database-specific security challenges
The competitive landscape for cloud database security spans established infrastructure and database vendors, cloud service providers, and specialized security firms, all competing to deliver integrated controls, managed detection, and compliance assurance. Leading vendors are investing in deeper integration with platform-native telemetry and identity systems to provide frictionless deployment and higher-fidelity detection. At the same time, specialist providers focus on threat analytics, database-specific anomaly detection, and automated remediation playbooks that reduce mean time to containment. Many companies are evolving toward offering both software and managed services to address varying customer preferences for in-house operations versus outsourced programs.
Partnerships and channel strategies play a pivotal role in market dynamics; technology alliances between database platform vendors and security providers speed time-to-value for customers, while managed service partnerships enable broader adoption among organizations with limited security headcount. Innovation is concentrated around automation, machine learning-driven detection, and policy-as-code capabilities that allow security teams to extend guardrails into development and deployment pipelines. Buyers should evaluate vendors not only on feature sets but also on integration depth, operational support models, and their ability to demonstrate consistent, repeatable outcomes in customer environments.
Actionable recommendations for executives to operationalize cloud database security through inventory-driven policies, identity-first controls, encryption, and vendor risk resilience
Industry leaders must adopt a pragmatic, prioritized approach to harden cloud database estates while enabling business agility. First, establish an authoritative inventory and classification of all database assets, including the various non-relational and relational engines, along with their deployment model and access patterns. This inventory becomes the single source of truth to drive policy enforcement, threat hunting, and recovery planning. Second, align identity and access management with least-privilege principles and implement continuous validation of role assignments and service principals to prevent privilege drift. Third, embed encryption and key management across data at rest and in motion, while ensuring that backup and recovery processes are resilient and regularly tested for integrity and speed of restoration.
Leaders should also adopt policy-as-code and integrate security checks into CI/CD pipelines to prevent insecure configurations from reaching production. Invest in high-fidelity detection tailored to database telemetry and apply threat hunting techniques that consider both SQL-based and application-layer exfiltration vectors. Finally, formalize vendor risk management practices that account for tariff and supply chain exposures, and design procurement strategies that prioritize software portability and multi-vendor redundancy. These steps, when sequenced and governed with executive sponsorship, materially reduce operational risk and improve response effectiveness.
Explaining the rigorous hybrid research methodology that blends practitioner interviews, technical analysis, and documented validation to produce defensible cloud database security insights
The research methodology relied on a hybrid approach combining qualitative and quantitative data gathering, structured interviews with practitioners and solution providers, and analysis of publicly available technical documentation and regulatory guidance. Primary engagements focused on security architects, database administrators, procurement leaders, and incident responders to capture firsthand operational challenges and validated best practices. Secondary research synthesized vendor materials, technical whitepapers, and regulatory texts to triangulate technical requirements and governance expectations.
Analytical techniques included thematic coding of interview transcripts to identify recurring capability gaps and success factors, and comparative feature mapping across solution categories to evaluate integration and delivery models. The methodology emphasized transparency and reproducibility by documenting source types and the rationale for analytical choices, while ensuring that recommendations reflect observed practices and defensible interpretation rather than market sizing assumptions. Limitations include variability in disclosure across vendors and organizations and the rapidly changing nature of cloud platform features, which the methodology mitigated through multiple rounds of validation with domain experts.
Concluding the executive synthesis by emphasizing the enduring nature of cloud database security as an engineering discipline enabled by governance, automation, and cross-functional alignment
In summary, cloud database security demands a strategic, capability-driven response that recognizes the diversity of database technologies, deployment models, and industry obligations. Organizations that treat database protection as an engineering and governance priority will reduce exposure to sophisticated exfiltration attempts and accelerate their ability to recover from disruptive incidents. The combination of identity-first controls, automation in deployment pipelines, and high-fidelity detection tailored to database telemetry forms the core of a resilient security approach.
Moreover, external forces such as trade policy shifts and regional regulatory divergence necessitate that security programs remain adaptive, with procurement and legal teams closely aligned to technical decision-making. By prioritizing inventory accuracy, policy-as-code, encryption, and vendor diversification, enterprises can preserve both performance and assurance as they modernize their data architectures. The conclusion is clear: protecting databases in the cloud is not a one-time project but an ongoing engineering discipline that requires executive sponsorship, cross-functional collaboration, and measurable governance.
Note: PDF & Excel + Online Access - 1 Year
Framing the strategic imperative for cloud database security by synthesizing migration dynamics, threat evolution, regulatory pressures, and operational resilience requirements
Cloud database security sits at the intersection of modern data strategy and relentless threat activity, shaping how organizations protect critical assets while pursuing digital transformation. The rapid adoption of cloud-native architectures, containerized platforms, and distributed data stores has reshaped the perimeter and increased the attack surface, requiring security teams to rethink legacy controls and embed protection directly into data lifecycles. This introduction distills the drivers, constraints, and operational imperatives that should inform board-level discussions and security investment decisions.
As enterprises migrate diverse database workloads to cloud, they face a complex set of trade-offs between scalability, performance, and control. Data residency and compliance expectations layer additional obligations on architecture and procurement choices. Meanwhile, threat actors increasingly target database endpoints for high-value exfiltration and ransomware staging, emphasizing the need for observability, least-privilege access models, and resilient recovery capabilities. Taken together, these forces underscore why cloud database security must transition from a tactical checklist to a strategic competency embedded across engineering, operations, and risk management.
Identifying the primary transformative shifts redefining cloud database security including identity-first controls, diverse data models, DevSecOps integration, and supply chain constraints
The landscape of cloud database security is undergoing several transformative shifts that alter both risk profiles and defensive responsibilities. First, control planes and orchestration layers have become as valuable a target as the data stores themselves; attackers exploit misconfigurations and weak identity management at scale, prompting a shift toward identity-first security and continuous configuration validation. Organizations must therefore prioritize inventory accuracy and real-time posture assessment as foundational capabilities.
Second, the proliferation of non-relational database technologies, event-driven architectures, and multi-model stores has created diverse telemetry and protection requirements. Security architectures can no longer assume uniform APIs or access patterns; defenders must instrument bespoke controls and threat detection for document, graph, key-value, wide-column, and traditional relational engines. Third, the convergence of DevOps and security practices has elevated the importance of shift-left controls and automated policy enforcement within CI/CD pipelines. Finally, supply chain considerations and geopolitical dynamics are introducing new constraints on vendor sourcing and hardware procurement, requiring security and procurement teams to coordinate closely to preserve both performance and assurance.
Analyzing how United States tariff measures in 2025 are reshaping procurement economics, vendor delivery models, and architectural choices across cloud database security
The cumulative impact of recently announced tariffs and trade policy adjustments in the United States for 2025 has introduced material effects across the cloud database security ecosystem, influencing hardware procurement, vendor economics, and operational planning. Higher duties on select hardware components and networking gear increase total cost of ownership for on-premises and hybrid deployments, making public cloud services comparatively attractive while simultaneously pressuring cloud providers to optimize supply chains and component sourcing. This dynamic encourages greater scrutiny of where and how database workloads run and underscores the value of cloud-native security services that reduce dependency on custom hardware stacks.
In addition, tariffs affect the economics of appliance-based security solutions and specialized database protection appliances, prompting vendors to adapt their delivery models toward software-centric, subscription-driven offerings and managed services. Risk and compliance teams are responding by reassessing contractual clauses, SLAs, and vendor continuity plans to account for potential supplier disruptions and longer lead times. The net effect is an acceleration of architectural decisions that favor elasticity, portability, and software-defined security controls, while increasing the importance of vendor diversification and rigorous third-party risk management.
Delivering actionable segmentation insights across database types, organizational scale, deployment models, security services, and industry vertical constraints informing tailored security postures
Granular segmentation provides clarity on how security needs diverge across database types, organizational scale, deployment patterns, security services, and end-user industries. Security posture and required tooling vary significantly based on whether workloads run on non-relational stores versus relational engines; non-relational environments introduce distinct telemetry and access patterns across document, graph, key-value, and wide-column formats, while relational environments require tailored controls for engines such as MySQL, Oracle, PostgreSQL, and SQL Server. This technological heterogeneity requires security strategies that combine generic hardening practices with engine-specific threat detection and policy sets.
Organization size further differentiates capability needs and procurement models: large enterprises often demand integrated governance, advanced forensics, and vendor-managed services, whereas small and medium-sized enterprises frequently prefer turnkey solutions that reduce operational overhead and simplify compliance. Deployment model choices-hybrid cloud, private cloud, and public cloud-shape where responsibility for security lies and what controls are feasible; hybrid models emphasize consistent policy enforcement across on-prem and cloud, private clouds prioritize control and isolation, and public clouds shift more responsibility to managed service offerings and provider-native tools. The security service taxonomy-access control, backup and recovery, compliance and auditing, data encryption, database firewall, and threat detection-maps directly to risk scenarios and maturity levels, enabling organizations to prioritize investments against their highest exposures. Finally, end-user industries such as BFSI, government and defense, healthcare, IT and telecom, and retail and e-commerce present distinct regulatory, data privacy, and availability constraints, which should drive sector-specific control frameworks and incident response playbooks.
Explaining regional variations in cloud database security priorities and how regulatory, provider, and geopolitical forces shape protective architectures across global markets
Regional dynamics influence threat landscapes, regulatory regimes, and vendor ecosystems, producing divergent priorities and approaches to cloud database security. In the Americas, regulatory emphasis on data protection and evolving breach notification laws coexist with a competitive cloud provider market and a vibrant ecosystem of security startups, which together encourage rapid adoption of advanced monitoring, encryption, and managed detection capabilities. Organizations in this region frequently prioritize integration with existing compliance regimes and value practical, operational controls that enable rapid incident containment and forensic analysis.
In Europe, the Middle East & Africa, heightened regulatory scrutiny around data privacy and cross-border transfers compels organizations to emphasize data residency, encryption, and rigorous access governance, while regional fragmentation in legal frameworks necessitates adaptable, policy-driven security solutions. The Asia-Pacific region presents a complex mix of high-growth cloud adoption and substantial domestic cloud provider footprints; regional variations in regulatory expectations and infrastructure resilience demand flexible architectures that can deliver both performance and compliance. Across all regions, geopolitical considerations, local supply chain dynamics, and talent availability shape the selection and deployment of security controls and managed service relationships.
Profiling how vendors and service providers are differentiating through integration depth, managed services, analytics, and automation to solve database-specific security challenges
The competitive landscape for cloud database security spans established infrastructure and database vendors, cloud service providers, and specialized security firms, all competing to deliver integrated controls, managed detection, and compliance assurance. Leading vendors are investing in deeper integration with platform-native telemetry and identity systems to provide frictionless deployment and higher-fidelity detection. At the same time, specialist providers focus on threat analytics, database-specific anomaly detection, and automated remediation playbooks that reduce mean time to containment. Many companies are evolving toward offering both software and managed services to address varying customer preferences for in-house operations versus outsourced programs.
Partnerships and channel strategies play a pivotal role in market dynamics; technology alliances between database platform vendors and security providers speed time-to-value for customers, while managed service partnerships enable broader adoption among organizations with limited security headcount. Innovation is concentrated around automation, machine learning-driven detection, and policy-as-code capabilities that allow security teams to extend guardrails into development and deployment pipelines. Buyers should evaluate vendors not only on feature sets but also on integration depth, operational support models, and their ability to demonstrate consistent, repeatable outcomes in customer environments.
Actionable recommendations for executives to operationalize cloud database security through inventory-driven policies, identity-first controls, encryption, and vendor risk resilience
Industry leaders must adopt a pragmatic, prioritized approach to harden cloud database estates while enabling business agility. First, establish an authoritative inventory and classification of all database assets, including the various non-relational and relational engines, along with their deployment model and access patterns. This inventory becomes the single source of truth to drive policy enforcement, threat hunting, and recovery planning. Second, align identity and access management with least-privilege principles and implement continuous validation of role assignments and service principals to prevent privilege drift. Third, embed encryption and key management across data at rest and in motion, while ensuring that backup and recovery processes are resilient and regularly tested for integrity and speed of restoration.
Leaders should also adopt policy-as-code and integrate security checks into CI/CD pipelines to prevent insecure configurations from reaching production. Invest in high-fidelity detection tailored to database telemetry and apply threat hunting techniques that consider both SQL-based and application-layer exfiltration vectors. Finally, formalize vendor risk management practices that account for tariff and supply chain exposures, and design procurement strategies that prioritize software portability and multi-vendor redundancy. These steps, when sequenced and governed with executive sponsorship, materially reduce operational risk and improve response effectiveness.
Explaining the rigorous hybrid research methodology that blends practitioner interviews, technical analysis, and documented validation to produce defensible cloud database security insights
The research methodology relied on a hybrid approach combining qualitative and quantitative data gathering, structured interviews with practitioners and solution providers, and analysis of publicly available technical documentation and regulatory guidance. Primary engagements focused on security architects, database administrators, procurement leaders, and incident responders to capture firsthand operational challenges and validated best practices. Secondary research synthesized vendor materials, technical whitepapers, and regulatory texts to triangulate technical requirements and governance expectations.
Analytical techniques included thematic coding of interview transcripts to identify recurring capability gaps and success factors, and comparative feature mapping across solution categories to evaluate integration and delivery models. The methodology emphasized transparency and reproducibility by documenting source types and the rationale for analytical choices, while ensuring that recommendations reflect observed practices and defensible interpretation rather than market sizing assumptions. Limitations include variability in disclosure across vendors and organizations and the rapidly changing nature of cloud platform features, which the methodology mitigated through multiple rounds of validation with domain experts.
Concluding the executive synthesis by emphasizing the enduring nature of cloud database security as an engineering discipline enabled by governance, automation, and cross-functional alignment
In summary, cloud database security demands a strategic, capability-driven response that recognizes the diversity of database technologies, deployment models, and industry obligations. Organizations that treat database protection as an engineering and governance priority will reduce exposure to sophisticated exfiltration attempts and accelerate their ability to recover from disruptive incidents. The combination of identity-first controls, automation in deployment pipelines, and high-fidelity detection tailored to database telemetry forms the core of a resilient security approach.
Moreover, external forces such as trade policy shifts and regional regulatory divergence necessitate that security programs remain adaptive, with procurement and legal teams closely aligned to technical decision-making. By prioritizing inventory accuracy, policy-as-code, encryption, and vendor diversification, enterprises can preserve both performance and assurance as they modernize their data architectures. The conclusion is clear: protecting databases in the cloud is not a one-time project but an ongoing engineering discipline that requires executive sponsorship, cross-functional collaboration, and measurable governance.
Note: PDF & Excel + Online Access - 1 Year
Table of Contents
180 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Adoption of unified data encryption and key management solutions across multi-cloud database environments
- 5.2. Integration of runtime data masking and dynamic obfuscation for real-time analytics in cloud data warehouses
- 5.3. Automated detection and remediation of misconfigurations in cloud-native database services using AI-driven security platforms
- 5.4. Implementation of zero-trust network segmentation for microservices-based distributed databases in the cloud
- 5.5. Use of homomorphic encryption for enabling secure computation on sensitive data in cloud database applications
- 5.6. Real-time streaming anomaly detection of database activity logs for threat hunting in serverless database architectures
- 5.7. Compliance automation for cross-border data residency and sovereignty requirements in cloud-hosted databases
- 5.8. Deployment of agentless database auditing integrated with DevOps pipelines for continuous security assurance in CI/CD workflows
- 5.9. Emergence of collaborative schema governance platforms to prevent injection risks in multi-tenant cloud databases
- 5.10. Integration of blockchain-based audit trails for tamper-proof logging of access and modifications in cloud database systems
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Cloud Database Security Market, by Database Type
- 8.1. Non-Relational
- 8.1.1. Document
- 8.1.2. Graph
- 8.1.3. Key-Value
- 8.1.4. Wide-Column
- 8.2. Relational
- 8.2.1. MySQL
- 8.2.2. Oracle
- 8.2.3. PostgreSQL
- 8.2.4. SQL Server
- 9. Cloud Database Security Market, by Security Service
- 9.1. Access Control
- 9.2. Backup And Recovery
- 9.3. Compliance And Auditing
- 9.4. Data Encryption
- 9.5. Database Firewall
- 9.6. Threat Detection
- 10. Cloud Database Security Market, by End User
- 10.1. BFSI
- 10.2. Government And Defense
- 10.3. Healthcare
- 10.4. IT And Telecom
- 10.5. Retail And E-Commerce
- 11. Cloud Database Security Market, by Deployment Model
- 11.1. Hybrid Cloud
- 11.2. Private Cloud
- 11.3. Public Cloud
- 12. Cloud Database Security Market, by Organization Size
- 12.1. Large Enterprises
- 12.2. Small & Medium-Sized Enterprises
- 13. Cloud Database Security Market, by Region
- 13.1. Americas
- 13.1.1. North America
- 13.1.2. Latin America
- 13.2. Europe, Middle East & Africa
- 13.2.1. Europe
- 13.2.2. Middle East
- 13.2.3. Africa
- 13.3. Asia-Pacific
- 14. Cloud Database Security Market, by Group
- 14.1. ASEAN
- 14.2. GCC
- 14.3. European Union
- 14.4. BRICS
- 14.5. G7
- 14.6. NATO
- 15. Cloud Database Security Market, by Country
- 15.1. United States
- 15.2. Canada
- 15.3. Mexico
- 15.4. Brazil
- 15.5. United Kingdom
- 15.6. Germany
- 15.7. France
- 15.8. Russia
- 15.9. Italy
- 15.10. Spain
- 15.11. China
- 15.12. India
- 15.13. Japan
- 15.14. Australia
- 15.15. South Korea
- 16. Competitive Landscape
- 16.1. Market Share Analysis, 2024
- 16.2. FPNV Positioning Matrix, 2024
- 16.3. Competitive Analysis
- 16.3.1. Alibaba Group
- 16.3.2. Amazon Web Services, Inc.
- 16.3.3. Delinea Inc.
- 16.3.4. Dell Technologies Inc.
- 16.3.5. EnterpriseDB Corporation
- 16.3.6. Forcepoint LLC
- 16.3.7. Fortanix, Inc.
- 16.3.8. Fortinet, Inc.
- 16.3.9. Google LLC by Alphabet Inc.
- 16.3.10. HCL Technologies Limited
- 16.3.11. Huawei Technologies Co., Ltd.
- 16.3.12. Imperva, Inc.
- 16.3.13. International Business Machines Corporation
- 16.3.14. JFrog Ltd.
- 16.3.15. Microsoft Corporation
- 16.3.16. NetSecurity Corporation
- 16.3.17. Netwrix Corporation
- 16.3.18. Progress Software Corporation
- 16.3.19. SentinelOne, Inc.
- 16.3.20. Singapore Telecommunications Limited
- 16.3.21. Sophos Holdings Limited
- 16.3.22. Syslink Xandria Ltd.
- 16.3.23. Tencent Holdings Ltd.
- 16.3.24. Trend Micro Incorporated
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