How Security Data Fabrics are Redefining Enterprise Security

A security data fabric is a type of architecture that integrates and manages security data from various sources in a unified, secure and governed approach. In other words, a data fabric is a data operational layer that not only brings all of the data into a single repository but also transforms and processes it using machine learning to discover patterns in behavior and deliver insights.

Collecting and managing security data is a persistent and costly problem. Most security operations centers (SOCs) are built around mature threat detection, investigation, and response (TDIR) solutions, commonly centered on a next-generation SIEM. While these solutions are the workhorses for log ingestion and analysis, they are expensive to operate, particularly regarding data retention costs, and they often lack the flexibility in data use and federation needed by modern enterprises.

Moving Beyond Pipeline Management

Data pipeline management tools have emerged, with SIEM augmentation as a primary use case. The purpose of these tools is to decouple the frontend data discovery and processing tasks from the SIEM architecture. By moving more intelligence into the pipeline, data storage decisions can be made before data routing decisions.

For organizations to embrace a fully federated data architecture, however, requires a more strategic rethinking of how security data is discovered, processed, connected, and consumed. This is where data fabrics can play an important role in modernizing how organizations utilize security data. Data fabrics typically support a broad set of capabilities in addition to pipeline management, most notably, data governance features such as data lineage.

The Market Landscape and Strategic Value

The overall market for security data management solutions continues to attract new entrants, investors, and acquisition interest. Omdia is tracking dozens of vendors that position themselves as solution providers for data fabrics, data pipeline management, or both. Data fabric vendors have been particularly focused on proactive security use cases, and data fabrics can act as a foundation for a host of Continuous Threat Exposure Management applications (see Figure 1).

Figure 1: Data fabrics are a foundational component of a new class of proactive security platforms

Source: Omdia

Deploying data fabrics should be viewed as a strategic initiative that can leverage the entire security stack. By taking a metadata-focused approach to data management, data fabrics simplify and often automate data discovery, access, and governance. This holistic, metadata-level view enables a consistent governance strategy across data sources and unifies data access and data security policies through centralized policy management.

Finally, and most importantly, data is made available for real-time analytics by any approved analytic engine or application. This democratization of data usage can significantly increase the value of existing security telemetry and reduce vendor lock-in and reliance on proprietary data schemas.

The Future of Data Ingestion

The future of data ingestion for cybersecurity data fabrics will focus on additional automation, with AI-powered agents playing a key role. They will learn how to connect, collect, and analyze the available data within each target for use within the context created by the fabric. They will possess the intelligence required to proactively discover all relevant data sources in a digital ecosystem, including previously unknown assets. The agent will be able to understand data semantics, adapt to evolving or changing APIs, and establish and learn new connections dynamically, resulting in a decrease in maintenance and total operational overhead. Already today, AI agents are being used very successfully to automate data normalization tasks, such as standardizing data in OCSF.

Source: Omdia

Omdia’s analysis divides the top vendors of security data fabrics and data pipeline management into a three-tier structure based on market penetration. Tier 1 comprises vendors with the widest market penetration, led by Microsoft. Imperva and Databee lead Tier 2 and Tier 3, respectively, based on market outreach within their specific tiers.

Source: Omdia

Source: Omdia

Source: Omdia