SOCRadar powers rapid threat detection with AlloyDB and Gemini Enterprise

Editor’s note: SOCRadar is a leading cybersecurity company that provides threat intelligence to businesses worldwide. As the volume of cyber threats continued to grow, SOCRadar needed to modernize its data infrastructure to deliver faster insights to its customers. By migrating from PostgreSQL to AlloyDB, SOCRadar achieved a 20x performance boost, reduced operational overhead, and is now better positioned to innovate and grow.

How SOCRadar supercharges rapid threat detection with AlloyDB 

SOCRadar provides external threat intelligence to help organizations across 30+ countries defend against cyberattacks. On the front lines of cybersecurity, timely intelligence is everything and a delay of a few minutes can mean the difference between a blocked exploit and a full-scale breach.

As SOCRadar’s business scaled and cyber threat volumes exploded, their on-premises, self-managed PostgreSQL database hit a wall. The database simply couldn’t keep pace with the simultaneous demands of high-velocity data ingestion and heavy, real-time analytical queries. This created a severe data bottleneck, slowing down the delivery of critical insights to customers and pulling engineers away from innovation to focus on constant manual database tuning.

Evaluating database alternatives: The hunt for scalability

The engineering team realized their traditional PostgreSQL environment had reached its absolute performance limits. To scale, SOCRadar needed a high-performance fully managed database that could dramatically slash operational overhead while elegantly handling a complex, hybrid workload.

They evaluated alternatives and selected Google Cloud’s AlloyDB for PostgreSQL. Because AlloyDB is fully PostgreSQL-compatible, it offered a low-risk migration path while promising a specialized architecture built to handle both high-volume transactions and real-time analytics simultaneously. To accelerate the transition, SOCRadar partnered with NGC, a Premier Business Partner, who meticulously validated the architecture before executing a precision cutover with minimal downtime.

Taming a “triple-threat” workload

Migrating to AlloyDB transformed how SOCRadar processes massive, diverse cyber telemetry. Today, AlloyDB effortlessly manages what SOCRadar’s engineering team calls a “triple-threat” query environment, maintaining sub-second lookup latency even as processing volumes scale.

To understand the performance leaps, it helps to separate the system’s velocity (handling live data streams) from its depth (analyzing historical data):

• High-Velocity Transactional Ingestion (OLTP): The platform constantly ingests real-time telemetry from thousands of disparate, fast-moving sources—including Dark Web forums, botnet logs, and social media feeds. AlloyDB handles these continuous INSERT and UPSERT operations with a 3.2x boost in live ingestion velocity, ensuring that the newest threat indicators are immediately recorded and available for detection.

• Real-Time Operational Point-Reads: When a security analyst is actively investigating a live incident, speed is everything. Baseline performance testing under zero-load conditions for random ID lookups on indexed fields (e.g., querying a specific Indicator of Compromise by ID) showed that standard queries requiring 3 to 3.5 seconds were completed in just 1 second on AlloyDB.

• Deep Analytical Aggregations (OLAP): When a client requests a complex sectoral report such as correlating the most prevalent attack vectors in the finance sector over an entire year, the database must execute deep scans across vast historical datasets. Leveraging AlloyDB’s built-in In-Memory Columnar Engine, these analytical queries run up to 20x faster than standard PostgreSQL.

More than just speed: Reclaiming 45 TB and 75% of DBA time

While the raw performance gains were massive, the operational and financial impact completely changed how SOCRadar’s engineering team works day-to-day.

Thanks to AlloyDB’s advanced automation, including intelligent memory management and write-ahead log (WAL) optimization, the need for constant, manual database tuning evaporated. The database administrator’s (DBA) workload dropped significantly, requiring a system health check just “about once every two or three days.” This freed up 75% of SOCRadar’s DBA resources, allowing them to pivot away from maintenance and focus entirely on core platform innovation.

Financially, AlloyDB’s dynamic storage management solved a massive cost efficiency issue. Unlike traditional database environments that lock you into paying for fixed, provisioned storage even after data is purged, AlloyDB automatically scales storage down to match actual data footprints. By clearing out legacy, unnecessary logs, SOCRadar was able to instantly reclaim over 45 TB of storage, achieving massive, automated cost optimization.

Fighting alert fatigue with integrated Gemini Enterprise Agent Platform

Beyond scaling infrastructure, AlloyDB has allowed SOCRadar to redefine the core architecture of their threat response using artificial intelligence.

Security operations centers (SOCs) globally are plagued by “alert fatigue”—the sheer volume of security alarms makes it easy to miss a critical attack. To solve this, SOCRadar integrated Gemini Enterprise Agent Platform as a core component of their solution architecture, linking it directly to their Alarm Management framework running on AlloyDB.

By running Gemini AI-native filtering directly on their active data workloads, SOCRadar can automatically distinguish between true positives and benign false alarms. The AI categorizes, filters, and routes alerts before they ever reach the end-user. This ensures security analysts are insulated from noise and receive only the most critical, validated, and actionable intelligence.

By running Gemini AI-native filtering directly on their active data workloads, SOCRadar can automatically distinguish between true positives and benign false alarms. The AI categorizes, filters, and routes alerts before they ever reach the end-user. This ensures security analysts are insulated from noise and receive only the most critical, validated, and actionable intelligence, laying the groundwork for fully autonomous security operations.

Expanding capabilities: The future of agentic threat hunting

With a high-performance foundation firmly established, SOCRadar’s dedicated AI team is transitioning from passive analytics to active automation. The company is currently testing Agentic AI workloads, with plans to roll them into production in subsequent phases.

By integrating Real-time Data Agents with Gemini Enterprise and AlloyDB, SOCRadar is transforming with autonomous agents that don’t just store data, but actively hunt threats, reason over context, and take action. Their upcoming production roadmap includes:

• Natural Language Querying (NLQ): Allowing analysts to conduct rapid threat hunting using conversational language, lowering the technical barrier to querying massive database sets.

• Intelligent Semantic Similarity Search: Leveraging native vector embeddings and Gemini Enterprise to allow Data Agents to independently surface hidden patterns across historical logs that traditional keyword searches would miss.

• Automated Incident Summarization: Instantly transforming hundreds of lines of complex, deeply technical logs into concise, plain-language executive summaries for security analysts during critical incidents.

By consolidating transactional velocity, historical depth, and built-in AI intelligence into a unified platform, SOCRadar has eliminated its data bottlenecks and built a highly automated, future-proof framework for global cybersecurity defense.

Ready to modernize your database infrastructure? AlloyDB provides a fully managed, PostgreSQL-compatible database with high performance for transactional, analytical, and AI workloads. Learn how you can reduce costs, eliminate management overhead, and build intelligent applications.