Cyber Lakehouses with Starburst

Cyber Threats Are Evolving Faster Than Your Data Strategy – And Your Tools Can’t Keep Up.

Let’s be honest: many organisations are facing significant challenges in managing cyber data effectively

Security Operations Centres (SOCs) are overwhelmed by vast amounts of data, making it difficult to identify and respond to threats efficiently. Many rely on outdated architectures and costly SIEM solutions that struggle to deliver actionable intelligence at the speed required to combat modern cyber threats. Meanwhile, attackers continue to evolve, leveraging AI and automation to stay ahead.

The result? Security teams are trying to defend against next-generation threats with legacy tools, creating a critical gap in cybersecurity resilience.

The Data Crisis in Security Operations Centres (SOCs)

Today’s SOCs are tasked with detecting, investigating, and neutralizing sophisticated threats in real time. However, many struggle with outdated infrastructure, fragmented data, and inefficient processes. These challenges create operational delays, increase exposure to cyber threats, and weaken overall defence capabilities.

Here’s why:

• Limited Data Retention – Traditional SIEMs typically store only 90 days of data, making long-term threat analysis and compliance difficult. Without historical visibility, SOCs struggle to identify emerging attack trends, detect persistent threats, and conduct thorough forensic investigations. This limitation leaves organizations vulnerable to adversaries who operate over extended timelines.
• Fragmented & Incomplete Data – Security telemetry is scattered across cloud, on-premises, and third-party tools, leading to critical visibility gaps. Instead of focusing on proactive threat hunting, security teams spend valuable time piecing together disparate data sources. Attackers exploit these blind spots, moving undetected across environments.
• Slow Incident Response – Legacy systems weren’t designed to efficiently process today’s massive datasets. As a result, investigations take longer, delaying detection, analysis, and remediation. This extended response time increases the risk of threats spreading before they can be contained.
• Lack of AI/ML Integration – Many SIEMs were not built for AI-driven threat detection, leaving SOCs at a disadvantage. Without AI-powered insights, security teams must rely on manual correlation, making it difficult to keep pace with rapidly evolving attacks.
• Rising Costs – SIEM pricing models based on data ingestion often force teams to limit log collection to control costs. This trade-off between affordability and visibility results in incomplete security data, weakening analytics and increasing operational risk.
• Vendor Lock-In – Many legacy solutions operate within closed ecosystems, limiting flexibility and integration with best-in-class security tools. This dependence on a single vendor’s roadmap and pricing model restricts organizations from tailoring their security approach to their unique needs.

To keep pace with modern threats, organizations need a more adaptive, scalable, and intelligent approach to cybersecurity operations.

The Need for a New Cyber Data Architecture

To combat today’s cyber threats effectively, SOCs must rethink how they manage security data. Data is the foundation of modern cybersecurity, driving real-time threat detection, AI-powered intelligence, and comprehensive visibility across all environments. Without a robust data strategy, security teams face blind spots, slow investigations, and incomplete threat analysis.

A modern cyber data architecture should provide:

• Real-Time Threat Detection – Instant analysis and response to security events, enabling proactive threat mitigation before incidents escalate.
• Comprehensive Data Retention – Long-term storage of security telemetry to support trend analysis, forensic investigations, and regulatory compliance.
• AI and Machine Learning Integration – Native support for AI/ML-driven analytics to automate threat detection, risk scoring, and anomaly identification.
• Unified Visibility Across All Environments – A seamless, holistic view of security data across cloud, on-prem, and hybrid environments to eliminate blind spots.
• Scalability & Adaptability – The flexibility to scale based on evolving cyber threats and changing business needs.
• Seamless Data Correlation & Enrichment – The ability to merge and analyse disparate datasets, providing deeper context and more actionable intelligence.
• High-Performance Querying & Analytics – Rapid access to both real-time and historical security data, allowing SOCs to conduct complex investigations without delays.
• Cost Efficiency – A sustainable pricing model that enables organizations to maximize visibility without sacrificing valuable security data.
• Open, Vendor-Agnostic Architecture – Freedom from vendor lock-in, enabling integration with best-in-class security tools and future innovations.

By adopting these capabilities, organizations can shift from a reactive to a proactive cybersecurity posture—enhancing efficiency, reducing risk, and strengthening resilience against evolving threats.

Introducing the Cyber Lakehouse: The Future of Cybersecurity Data Management

The Cyber Lakehouse combines the strengths of SIEMs, data lakes, and data warehouses—delivering the scale, visibility, and efficiency that modern SOCs require. By overcoming the limitations of traditional architectures and harnessing the full power of security data, this approach gives SOCs the agility and intelligence needed to combat today’s evolving cyber threats. It enables security teams to unify and analyse structured and unstructured data at an unprecedented scale while integrating AI-driven insights for faster detection and response.

Here’s how it transforms cybersecurity operations:

• Breaking Free from SIEM Limitations – Traditional SIEMs charge based on data ingestion, making it costly to retain and analyse security data. A Lakehouse eliminates volume-based pricing constraints, allowing SOCs to store and process vast datasets affordably.
• AI-Driven Threat Detection – Cyber threats evolve over time, often spanning weeks or months. A Lakehouse integrates AI and machine learning analytics to detect attack patterns early, enabling SOCs to neutralize threats before they escalate.
• Unified Data Management & Visibility – While SIEMs handle structured data and data lakes store unstructured data, a Lakehouse bridges both—creating a single platform for all security telemetry, logs, and alerts.
• Faster Threat Hunting & Incident Response – Instant access to both real-time and historical data accelerates investigations, enabling SOCs to proactively hunt threats, perform rapid forensic analysis, and significantly reduce response times.
• Compliance & Regulatory Support – Regulations such as GDPR, CCPA, HIPAA, and PCI-DSS require long-term data retention. A Cyber Lakehouse provides scalable, cost-effective storage to meet compliance requirements without excessive costs.
• Enhanced Data Enrichment & Correlation – By aggregating data from multiple sources—such as endpoint detection and response (EDR) tools, identity and access management (IAM) logs, and network telemetry—a Lakehouse enhances threat intelligence and attack pattern recognition.
• Vendor-Agnostic, Open Architecture – Unlike traditional SIEMs that lock organizations into proprietary ecosystems, a Cyber Lakehouse enables seamless integration with modern security tools, providing greater flexibility.
• Powering the AI-Driven SOC 2.0 – As SOCs evolve toward AI-driven security operations, a Lakehouse supports real-time risk scoring, automated threat responses, and predictive analytics—enhancing efficiency and strengthening proactive defence.

By adopting the Cyber Data Lakehouse, organizations can modernize their cybersecurity operations, gaining the scale, intelligence, and cost efficiency needed to stay ahead of evolving threats.

Starburst: The Solution for a Cost-Effective Cyber Lakehouse-

As a seamless extension to existing cyber analytics architectures, Starburst delivers a cost-effective Cyber Lakehouse that expands SOC visibility beyond the typical 90-day retention limit—allowing security teams to store, analyse, and act on years of security data without excessive costs. By combining low-cost storage, high-performance querying, and AI-ready data federation, Starburst optimizes security data management while maintaining compliance across cloud and on-prem environments. Cyber Data Products—curated, reusable datasets representing the most commonly accessed security information—enable SOCs to quickly locate, correlate, and analyse critical data for investigations and threat detection. These structured data assets accelerate AI-driven security operations, reducing investigation time and improving operational efficiency. Seamlessly integrating with existing SIEMs, data lakes, and multi-cloud environments, Starburst extends the value of current security investments while providing the scalability and flexibility needed to adapt to evolving threats, regulations, and architectures.

Future-Proof Your Cyber Strategy with a Cyber Lakehouse

The speed and sophistication of cyber threats demand a new approach. A Cyber Data Lakehouse extends SOC visibility, reduces costs, and enhances AI-driven security analytics—ensuring your organization stays ahead in the evolving cyber battlefield.

The question isn’t if you need a Cyber Lakehouse. It’s how soon can you implement it?