Leadership Compass

Database and Big Data Security

This Leadership Compass provides an overview of the market for database and big data security solutions along with guidance and recommendations for finding the sensitive data protection and governance products that best meet your requirements. We examine the broad range of technologies involved, vendor product and service functionality, relative market shares, and innovative approaches to implementing consistent and comprehensive data protection across your enterprise.

Alexei Balaganski


1 Introduction

Databases are arguably still the most widespread technology for storing and managing business-critical digital information. Manufacturing process parameters, sensitive financial transactions, or confidential customer records - all this valuable corporate data must be protected against compromises of their integrity and confidentiality without affecting their availability for business processes.

As more and more companies are embracing digital transformation, the challenges of securely storing, processing, and exchanging digital data continue to multiply. With the average cost of a data breach reaching $4M, just direct financial losses can be catastrophic for many companies, not even considering indirect reputational damages. High-profile “mega-breaches” that expose millions of sensitive data records can easily drive these costs up to hundreds of millions of dollars, but even the victims of smaller ones are now facing increasingly harsh compliance fines.

Nowadays, most companies end up using various types of databases and other data stores for structured and unstructured information depending on their business requirements. Recently introduced data protection regulations like the European Union’s GDPR or California’s recently approved CPRA (the new Privacy Rights Act will bring California’s legislation much closer to a GDPR equivalent) make no distinction between relational databases, data lakes, or file stores – all data is equally sensitive regardless of the underlying technology stack. Just keeping track of all the digital information is a big problem, but understanding which data is more sensitive according to various policies and regulations and then selecting and enforcing the necessary data protection and governance capabilities is already too much even for the largest businesses.

The area of database security covers various security controls for the information itself stored and processed in database systems, underlying computing and network infrastructures, as well as applications accessing the data. These include, among others, data protection capabilities, fine-grained access controls, activity monitoring, audit, and compliance features as well as other means needed for comprehensive multi-layered protection against external and internal threats. As the amount and variety of digital information managed by organizations continue to grow, the complexity of the IT infrastructure needed to support this digital transformation grows as well.

Among the security risks databases of any kind are potentially exposed to are the following:

  • Denial of service attacks leading to disruption of legitimate access to data.
  • Data corruption or loss through human errors, programming mistakes, or sabotage.
  • Inappropriate access to sensitive data by administrators or other accounts with excessive privileges.
  • Malware, phishing, and other types of cyberattacks that compromise legitimate user accounts.
  • Unpatched security vulnerabilities or configuration problems in the database software, which may lead to data loss or availability issues.
  • Attacks specifically crafted to target databases through application interfaces or APIs, like SQL injections for relational databases and similar exploits for NoSQL and Big Data solutions.
  • Sensitive data exposure due to poor data lifecycle management. This includes improperly protected backups, testing or analytical data without proper masking, etc.
  • Unsanctioned access to encrypted sensitive data due to improper key management – this is especially critical for cloud environments where encryption is often managed by the cloud service provider.
  • Insufficient monitoring and auditing – not only these pose a significant noncompliance risk, but a lack of a tamper-proof audit trail also makes forensic investigations and incident response much more complicated.

Consequently, multiple technologies and solutions have been developed to address these risks, as well as provide better activity monitoring and threat detection. Covering all of them in just one product rating would be quite difficult. Furthermore, KuppingerCole has long stressed the importance of a strategic approach to information security.

Therefore, 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.

1.1 Market Segment

Because of the broad range of technologies involved in ensuring comprehensive data protection, the scope of this market segment is not that easy to define unambiguously. Only the largest vendors can afford to dedicate enough resources for developing a solution that covers all or at least several functional areas – most products mentioned in this Leadership Compass tend to focus on one major aspect of database security like data encryption, access management, or monitoring and audit.

The obvious consequence of this is that when selecting the best solution for your requirements, you should not limit your choice to overall leaders of our rating – in fact, a smaller vendor with a lean, but flexible, scalable, and agile solution that can quickly address a specific business problem may be more fitting. On the other hand, one must always consider the balance between a well-integrated suite from a single vendor and several best-of-breed individual tools that require additional effort to make them work together. Individual evaluation criteria used in KuppingerCole’s Leadership Compasses will provide you with further guidance in this process.

To make your choice even easier, we are focusing primarily on security solutions for protecting structured and semi-structured data stored in relational or NoSQL databases, as well as in Big Data stores. Secondly, we are not explicitly covering various general aspects of network or physical server security, identity and access management, or other areas of information security not specific for databases, although providing these features or offering integrations with other security products may influence our ratings.

Still, we are putting a strong focus on integration into existing security infrastructures to provide consolidated monitoring, analytics, governance, or compliance across multiple types of information stores and applications. Most importantly, this includes integrations with SIEM/SoC solutions, existing identity, and access management systems, and information security governance technologies.

Solutions offering support for multiple database types as well as extending their coverage to other types of digital information are expected to receive more favorable ratings as opposed to solutions tightly coupled only to a specific database (although we do recognize various benefits of such tight integration as well). The same applies to products supporting multiple deployment scenarios, especially in cloud-based and hybrid (mixing on-premises and cloud) infrastructures.

Another crucial area to consider is the development of applications based on the Security and Privacy by Design principles, which have recently become a legal obligation under the EU’s General Data Protection Regulation (GDPR) and similar regulations in other geographies. Database and big data security solutions can play an important role in supporting developers in building comprehensive security and privacy-enhancing measures directly into their applications.

Such measures may include transparent data encryption and masking, fine-grained dynamic access management, unified security policies across different environments, and so on. We are taking these functions into account when calculating vendor ratings for this report as well.

1.2 Delivery Models

Since most of the solutions covered in our rating are designed to offer comprehensive protection and governance for your data regardless of the IT environment it is currently located – in an on-premises database, a cloud-based data lake, or a distributed transactional system – the very notion of the delivery model becomes complicated as well.

Certain components of such solutions, especially the ones dealing with monitoring, analytics, auditing, and compliance can be delivered as managed services or directly from the cloud as SaaS, but most other functional areas require deployment close to the data sources, as software agents or database connectors, as network proxies or monitoring taps and so on. Especially with complex Big Data platforms, a security solution may require multiple integration points within the existing infrastructure.

1.3 Required Capabilities

When evaluating the products, besides looking at the aspects of

  • overall functionality
  • size of the company
  • number of customers
  • number of developers
  • partner ecosystem
  • licensing models
  • platform support

We also considered the following key functional areas of database security solutions:

  • Vulnerability assessment – not limited to just discovering known vulnerabilities in database products, but providing complete visibility into complex database infrastructures, detecting misconfigurations, and the means for assessing and mitigating these risks.
  • Data discovery and classification – although classification alone does not provide any protection, it serves as a crucial first step in defining proper security policies for different data depending on their criticality and compliance requirements.
  • Data-centric security – technologies such as data encryption at rest and in transit as well as enterprise key management, tokenization, static and dynamic data masking, and other methods for protecting data integrity and confidentiality and for ensuring regulatory compliance for sensitive data in cloud environments.
  • Monitoring and analytics – monitoring of database performance characteristics, as well as complete visibility in all access and administrative actions for each instance, including alerting and reporting functions. On top of that, advanced real-time analytics, anomaly detection, and SIEM integration can be provided.
  • Threat prevention – various methods of protection from cyber-attacks such as denial-of-service or SQL injection, mitigation of unpatched vulnerabilities, and other infrastructure-specific security measures.
  • Access Management – not just basic coarse-grained access controls to database instances, but more sophisticated dynamic policy-based access management based on various data or user attributes, identifying and removing excessive user privileges, managing shared and service accounts, as well as detection and blocking of suspicious user activities.
  • Audit and Compliance – offering advanced auditing mechanisms beyond native capabilities, centralized auditing and reporting across multiple database environments, enforcing separation of duties, as well as tools supporting forensic analysis and compliance audits.
  • Deployment and Scalability – although not a security feature per se, it is a crucial requirement for all database security solutions to be able to withstand high loads, minimize performance overhead, and to support deployments in high availability configurations; all these must be supported in on-prem, cloud and hybrid environments.
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