The Missing Layer in the Modern SOC: Why SIEMs Need a Real-Time Data Control Plane
- Ting Wang
- 1 hour ago
- 4 min read
The SOC Is Being Re-Architected
The SOCs are overwhelmed, not by a lack of tools, but by how and where security data is processed. Enterprises now ingest massive volumes of telemetry from endpoints, identity systems, cloud platforms, applications and networks. Most of this data is shipped directly into SIEMs (Security Information and Event Management) or analytics platforms before its security signal is established.
The result is a familiar pattern:
SIEM costs scale much faster than outcomes
Correlation and context arrive too late for real-time signal and action
Detection logic becomes embedded in proprietary platforms, increasing lock-in
Temporal context is lost before analytics ever run
SOCs are not failing at analytics. They are failing at producing decision-ready security signals early enough, scale enough, cheap enough.
This is why the SOC is being re-architected. Across the industry, several trends are converging:
SIEM + data lake architectures are replacing legacy monolithic SIEM systems
Storage and analytics are decoupled to break scale-versus-cost bottlenecks
Agentic SOC workflows are emerging, requiring clean, contextual, and stateful data
Microsoft Sentinel’s Data Lake, Snowflake- or Databricks-based security analytics, and platforms like XSIAM all point to the same conclusion:
Security is no longer primarily a tooling problem. It is a data problem, and more specifically, a data control problem.
Yet even in these next-generation architectures, a critical layer is still missing.
The Gap in Next-Generation SIEM Architectures
Despite very different designs, both models struggle with the same fundamental issue:
Too much raw data reaches the analytics layer before security signal is established.
Modern SIEM + data lake platforms excel at:
Cost-efficient long-term storage
Historical investigation and retroactive threat hunting
Large-scale analytics and agentic querying
At the same time, most SOCs have adopted telemetry pipelines to control ingestion cost and data movement.
Yet a critical gap remains:
Telemetry pipelines decide where data goes
SIEMs and data lakes decide what data means — after it arrives
What’s missing is a layer that can decide: What security signal the data represents, in real time—before it becomes expensive, delayed, or operationally overwhelming.
What Modern SOC Architectures Still Lack
Specifically, next-generation SOC architectures lack:
High-throughput, low-latency, stateful telemetry stream processing
Real-time correlation across identities, sessions, sequences, and time
A deterministic, explainable layer that produces decision-ready security signals
Without this layer, teams push increasingly complex logic downstream into SIEM analytics tiers or ad-hoc scripts—reintroducing cost, latency, and operational fragility.
This is where a new category is emerging. Importantly, this gap exists across both generations of SIEM:
Traditional monolithic SIEMs (e.g., Splunk), where parsing and correlation live inside expensive index and search layers
Next-generation security analytics platforms (e.g., Microsoft Sentinel, Snowflake- or Databricks-based analytics, XSIAM), where storage and analytics are decoupled but real-time decision logic is still downstream
Different architectures. Same missing layer. The missing layer is not another SIEM, nor another data lake.
It is a real-time security data control plane.
Security Data Control Plane: A Critical Use Case of the Operational Data Plane
Security is one of the clearest and most demanding examples of a broader architectural shift already underway.
Timeplus is fundamentally designed as a next-generation operational data plane, built to process high-volume, low-latency, stateful data streams where decisions must be made continuously in real time.
Within this broader vision, security and SOC workloads represent a high-value proof point, not the entirety of the platform.
The same characteristics that define modern security operations—massive data volume, strict latency requirements, stateful correlation, and deterministic outcomes—are increasingly required across observability, fraud detection, reliability automation, and real-time business intelligence.
In the SOC, this operational data plane manifests as a security data control plane: a layer that sits upstream of SIEMs and data lakes to establish meaning before downstream analysis and response.
This framing matters. It positions security not as a special case, but as evidence that the operational data plane is becoming foundational across modern systems.
What a Security Data Control Plane Does
A security data control plane sits upstream of SIEMs and data lakes and answers three questions in real time:
What data matters now?
How should it be normalized, enriched, and correlated?
Where should it go next — SIEM, data lake, Cloud storage, SOAR, AI Agents, or all of them?
Instead of treating security data as passive logs, the control plane treats it as live, stateful streams that continuously emit decision-ready security context.. This is the role Timeplus is purpose-built to fill.
Timeplus: Built for Real-Time Operational Data Pipelines
Timeplus is a high-performance, SQL-based streaming compute engine designed for real-time operational data pipelines.
In a next-generation SOC architecture, Timeplus operates before SIEM analytics and alongside security data lakes, producing security context at stream speed.
A Concrete Example: Decoupling a Traditional Splunk Pipeline
In many Splunk-centric SOCs, critical security logic is embedded directly inside the SIEM:
Field extraction via props.conf and transforms.conf
Lookups and calculated fields via search-time logic
Event types and tags defined through configuration
This works, until scale breaks it:
Executes at index-time or search-time
Is difficult to version and test
Becomes increasingly expensive as volume grows
Is often too slow for real-time detection
Timeplus externalizes this logic into real-time SQL streaming pipelines, upstream of the SIEM.
What was once scattered across configuration files becomes declarative, version-controlled pipelines that execute once, in real time, and feed multiple downstream systems.
The SIEM focuses on investigation and response—not raw data shaping, context generation and control.
The Takeaway
Modern SOCs do not fail at query analytics. They fail at establishing meaning context early enough.
As security architectures evolve toward decoupled storage, agentic workflows, and automation, a real-time security data control plane becomes mandatory. Timeplus is built to be that missing layer.
Ready to try Timeplus? Download a 30-day free trial, risk-free. See installation options here: timeplus.com/download.