Security & Compliance · Engineering, IT & AI
Should you build or buy SIEM?
Security Information and Event Management (SIEM) software collects, normalizes, and correlates log and event data from across an organization's infrastructure to detect threats, investigate incidents, and satisfy compliance reporting requirements. It ingests data from endpoints, network devices, cloud services, and applications, then applies detection rules and analytics to surface anomalies and trigger alerts.
The build-vs-buy decision for SIEM turns on whether your detection logic is specific enough to your environment that custom correlation rules outperform vendor defaults, and whether AI-driven security posture makes owning your own telemetry pipeline worth the significant engineering investment required; the specifics decide it.
Build it, buy it, or bridge?
When building makes sense
The case for building your own SIEM is strongest for organizations with dedicated security engineering teams and environments where Splunk's $2,000-3,500 per gigabyte per year pricing creates a real financial incentive to find an alternative. Wazuh is explicitly described as one of the most widely deployed security monitoring platforms, in documented production across regulated environments. Security Onion is a purpose-built enterprise security monitoring distribution. Together with OpenSearch Security Analytics and Graylog, the open-source SIEM stack covers log analysis, intrusion detection, correlation, and compliance reporting for teams with Linux administration expertise. The strategic argument worth tracking is that SIEM data is increasingly the input for AI-driven security posture analysis, which raises the value of owning your telemetry pipeline. The complication is that licensing is rarely the dominant cost: a documented Elastic deployment hit $600,000 annually once senior engineering time was priced in, and parser development and detection rule engineering require sustained investment from people who could be doing other things.
When buying makes sense
Buying SIEM earns its keep when security staff is limited and reducing analyst workload is the primary goal. Microsoft Sentinel's consumption pricing model is meaningfully cheaper than on-prem Splunk for many organizations, and its integration with the broader Microsoft security stack reduces the connector configuration burden. Sumo Logic's cloud-native architecture eliminates the infrastructure management overhead of self-hosted solutions. Commercial platforms also absorb threat intelligence updates automatically and ship pre-built SOAR integrations that take months to wire manually on an open-source stack. The real calculation is whether the licensing savings from a DIY approach outweigh the engineering cost of building and maintaining detection rules, parsers, and correlation logic — which consistently runs at two to three times the licensing figure when you count the fully loaded cost of the engineering team involved.
The desk read
Wazuh and Security Onion are both in documented production as enterprise SIEM infrastructure. Wazuh in particular is explicitly described as one of the most widely deployed security monitoring platforms, covering log analysis, intrusion detection, and compliance reporting across regulated environments. The open-source path is legitimate for organizations with security engineering capacity, and the licensing savings over Splunk at volume are real. Splunk's $2,000 to $3,500 per gigabyte per year pricing is a genuine grievance that data-lake architectures are starting to address.
The complication is that licensing is not the dominant cost. A custom Elastic SIEM deployment documented in the evidence ran $600,000 annually once senior engineer time was included. Parser development, detection rule engineering, and correlation logic require sustained investment from people who could be working on other things. Microsoft Sentinel's consumption model and Sumo Logic's cloud-native architecture are both meaningfully cheaper than on-prem Splunk without requiring a full in-house build. The strategic question worth tracking is that SIEM data is increasingly the training set for AI-driven security posture, which raises the value of owning your own data pipeline.
Vendors in SIEM
Each file covers what the product is, its funding history, and when the index last verified it alive.
Frequently asked
What is SIEM?
SIEM software collects, normalizes, and correlates log and event data from across an organization's infrastructure to detect threats, investigate incidents, and satisfy compliance reporting requirements. It ingests data from endpoints, network devices, cloud services, and applications, then applies detection rules to surface anomalies.
When does building SIEM make sense?
Building is most defensible when Splunk's volume-based pricing creates a genuine cost incentive, your team has dedicated security engineering capacity, and you want to own your telemetry pipeline as an AI training asset. Wazuh and Security Onion are both in documented enterprise production.
When does buying SIEM make sense?
Buying earns its keep when security staff is limited, analyst workload reduction is the goal, and the engineering cost of maintaining detection rules would exceed the license savings. Microsoft Sentinel's consumption model undercuts on-prem Splunk for many environments without requiring a full in-house build.
What are the main SIEM vendors?
Representative vendors include Elastic Security, Microsoft Sentinel, Splunk, Sumo Logic Cloud SIEM. B4 Pro scores the full set.
What makes detection rules company-specific in SIEM?
Effective detection rules reflect your actual infrastructure topology, attack surface, compliance requirements, and incident history. Generic vendor rules miss context that only your environment provides — which is why security-mature organizations invest in custom rule engineering rather than relying entirely on out-of-box detections.