Database and Big Data Security

The Buyer’s Compass for Database and Big Data Security is a practical aid for narrowing vendor options during RFI/RFP cycles by aligning product selection with prioritized use cases, functional and non-functional criteria, prerequisites, and structured vendor questions. It is positioned as a starting point rather than a complete vendor-selection methodology, intended to help organizations shortlist candidates and proceed with deeper RFIs and proof-of-concepts while ensuring technical and organizational readiness.

The market context emphasizes that databases remain central to storing business-critical information and face diverse threats, including denial-of-service, human error, excessive privileges, compromised accounts, unpatched vulnerabilities, API-layer attacks (e.g., SQL injection), poor lifecycle handling of backups and test data, weak key management (notably in cloud), and insufficient monitoring and tamper-proof auditing. As digital transformation expands data volume and heterogeneity, the traditional boundary between “database” and “big data” is less meaningful for compliance: regulations treat “data as data,” and required protections depend on business context. Effective security therefore spans the full information protection lifecycle—from creation/discovery and classification through use and ultimately secure disposal or archival—using layered controls across data, infrastructure, and consuming applications.

Because no single capability covers all needs, organizations are encouraged to evaluate solutions as part of a multi-layered enterprise security architecture with centralized governance, management, and analytics, mindful that data moves across environments and technology stacks. The document outlines key use cases (IP protection, cloud migration, discovery/classification, access governance, incident response/breach notification, desensitization/disposal), maps these to functional criteria (e.g., threat prevention, monitoring, encryption, masking, automation), and complements them with vendor-oriented non-functional criteria (deployment models, ecosystem, compliance support, roadmap, maturity). It also highlights prerequisites such as hybrid deployment planning, measurable metrics, extensibility, skills, governance, ownership, training, SLAs, and risk-based policies.

• The average cost of a data breach reaches $4M.
• Mega-breaches can raise costs to hundreds of millions of dollars.
• Denial-of-service attacks can disrupt legitimate access to database data.
• Human errors, programming mistakes, or sabotage can corrupt or destroy data.
• Excessive privileges can enable inappropriate access to sensitive data by administrators or other accounts.
• Malware and phishing can compromise legitimate user accounts and lead to data exposure.
• Unpatched vulnerabilities or misconfigurations in database software can cause data loss or availability issues.
• SQL injection is identified as an example of an attack targeting relational databases via application interfaces or APIs.
• Poor lifecycle management can expose sensitive data through inadequately protected backups or unmasked test and analytical datasets.
• Improper encryption key management can enable unsanctioned access to encrypted sensitive data, especially in cloud environments.

• “You cannot protect what you don’t know”
• “Databases are arguably still the most widespread technology for storing and managing business-critical digital information.”
• “This document is not a complete guideline for selecting vendors but should provide an excellent starting point to streamline the decision-making process.”
• “Regulations like GDPR or CPRA make no distinction between SQL, NoSQL, data lakes of file servers – data is data, and the degree of protection it requires is only determined by its business context.”
• “Maintaining data classification throughout its complete lifecycle ensures that it will be properly managed and adequately protected at all times.”
• “Customers are encouraged to look at database and big data security products not as isolated point solutions, but as a part of an overall corporate security strategy based on a multi-layered architecture and unified by centralized management, governance, and analytics.”
• “The data seldom exists in a vacuum, isolated within just a single database, application, or network.”
• “Within a modern digital enterprise, it is constantly moving and transforming, passing through multiple IT environments, applications and services…”
• “Minimizing the potential impact of human error in database management… can have a massive impact on the Database-as-a-Service market.”
• “Some companies may struggle with these criteria, not because of technical weaknesses and wrong products, but because of a lack of organizational maturity.”