Wazuh vs Elastic Security (2026): Open-Source SIEM Pick

If you are building a modern, AI-augmented SOC on open-source tooling in 2026, the decision often comes down to Wazuh vs Elastic Security. This post compares them head to head, with a bias toward which one fits an AI-driven detection and response program. If you are weighing commercial SIEMs instead, see our Splunk vs Microsoft Sentinel breakdown.

The short answer

• Wazuh - pick this if you want a fully free, open-source XDR and SIEM with strong agent-based endpoint telemetry, file integrity monitoring, vulnerability detection, and built-in regulatory compliance mapping, all self-hosted. Best when host-level security and compliance coverage at zero license cost matter most.
• Elastic Security - pick this if you want a powerful, search-driven SIEM on the Elastic Stack with machine-learning anomaly detection, a mature detection-rules engine, and the Elastic Agent for EDR. Best when search depth, ML, and a managed-cloud option matter most.
• Both - used together when teams want Wazuh agents for free, deep host telemetry feeding into Elastic Security for search and ML-driven detection across all sources.

The rest of this post unpacks that decision in detail.

Deciding factor to pick

Match your priority to the recommendation. This is the Wazuh vs Elastic Security decision in one table:

If you only remember one rule: Wazuh is the free, self-hosted XDR and SIEM with deep host security and compliance, Elastic Security is the search-and-ML-driven SIEM with EDR on the Elastic Stack.

What each tool is

• Wazuh is a free, open-source security platform spanning XDR and SIEM, with fork lineage from OSSEC. It deploys lightweight agents on endpoints for log analysis, file integrity monitoring (FIM), vulnerability detection, intrusion detection, and regulatory compliance mapping, and ships a built-in dashboard. The dashboard historically ran on the Elastic Stack and current builds use OpenSearch for indexing and visualization, keeping the platform fully open source.
• Elastic Security is a SIEM and endpoint security solution built on the Elastic Stack (Elasticsearch and Kibana). It pairs fast search with a detection-rules engine, machine-learning anomaly detection, and the Elastic Agent for endpoint protection (EDR). It offers a free Basic tier you can self-host plus paid Platinum and Enterprise tiers and managed Elastic Cloud.

Wazuh vs Elastic Security: head-to-head

When to choose Wazuh

Pick Wazuh when:

• You want a fully free, open-source XDR and SIEM with no paid tier gating core capabilities.
• You need strong agent-based endpoint telemetry with log analysis, intrusion detection, and host-level visibility across servers and workstations.
• File integrity monitoring and vulnerability detection are first-class requirements you want built in, not bolted on.
• You need regulatory compliance mapping (such as PCI DSS, HIPAA, and similar frameworks) available out of the box.
• You are committed to self-hosting and want full control over where data lives and how the platform runs.
• You want a lean, OSSEC-derived stack that you can scale on your own infrastructure without per-feature licensing.

When to choose Elastic Security

Pick Elastic Security when:

• You want the most powerful search and analytics, and Elasticsearch query depth is a core requirement.
• You need machine-learning anomaly detection built into the SIEM to surface unusual behavior with less manual rule writing.
• You rely on a mature detection-rules engine with prebuilt and customizable rules for fast detection engineering.
• You want the Elastic Agent for EDR, unifying endpoint protection and SIEM telemetry in one stack.
• You already run the Elastic Stack for logs or observability and want security analytics on the same data.
• You want a managed-cloud option through Elastic Cloud, not only a self-hosted deployment.

Can you use them together?

Yes, and some teams do. The split we see:

• Wazuh agents for free, deep host telemetry - file integrity monitoring, vulnerability detection, intrusion detection, and compliance signal collected at the endpoint at zero license cost.
• Elastic Security for search and ML detection - forward that telemetry into Elasticsearch so Elastic’s detection rules and machine-learning jobs run across it alongside other sources.

This pairs Wazuh’s free, broad endpoint coverage with Elastic’s search and analytics power. The cost is added pipeline and storage complexity, so most teams eventually standardize detection logic on one platform to avoid duplicating rules and ingest. Whichever pair you run, the response automation matters more than the dashboards - see our work on AI Incident Response for building playbooks that investigate and contain threats in minutes.

Cost comparison

The real driver is operations and storage at scale, not a headline license, since both are open-source-friendly and self-hostable.

• Wazuh is free and open source with no license tier. Your spend is the infrastructure and the team time to run the manager, indexer (OpenSearch), and dashboard, plus retention storage.
• Elastic Security has a free Basic tier you can self-host, plus paid Platinum and Enterprise tiers and managed Elastic Cloud for advanced features and support. Total cost depends on whether you stay on the free tier or need paid features, plus the resource cost of running Elasticsearch at scale.

For a pure zero-license build, Wazuh wins on the headline. For Elastic, model whether free-tier features are enough or you need paid ML, support, or managed cloud. Standard SIEM cost controls apply to both: filter and route noisy data before ingestion, tier or archive low-value logs, and keep retention windows aligned to compliance rather than defaulting to keep-everything. Do not assume open source means free to operate - compute and storage dominate self-hosted SIEM cost.

Common pitfalls

• Assuming open source means no cost - both stacks are dominated by compute, storage, and operations expense at scale; budget for the team and infrastructure to run them.
• Choosing Wazuh expecting Elastic-grade search - Wazuh is excellent for host security and compliance, but if deep ad hoc search and ML anomaly jobs are central, Elastic is built for that.
• Choosing Elastic Security and skipping the free-tier check - confirm which features you need sit in Basic versus paid tiers before committing, so the bill does not surprise you.
• Skipping data normalization - an AI-augmented SOC is only as good as its normalized signal; detections and ML jobs misfire on messy, inconsistent data regardless of platform.
• Running both indefinitely by accident - duplicating detection rules and ingest across two platforms multiplies effort and storage; pick one primary system of record after you validate the pairing.

Related reading

• Splunk vs Microsoft Sentinel - the commercial SIEM equivalent of this decision
• QRadar vs Microsoft Sentinel - enterprise SIEM migration trade-offs
• AI-Powered SOC - how we operationalize an AI-augmented SOC on open-source stacks
• AI Security Posture Management - feeding normalized, high-signal data into your SIEM
• secops.qa blog - more on AI security operations and defending AI with AI

Getting help

We build AI-augmented security operations on open-source stacks like Wazuh and Elastic Security - the right one depends on your endpoints, your data, and how aggressively you want to automate detection and response. Our AI-Powered SOC engagement picks the platform, wires up detections and automation, and stands up analyst workflows so your SOC defends AI with AI from day one.

Book a free scope call.