Directory Observability & MonitoringLog Management & AnalyticsGraylog

Graylog

About Graylog

Graylog provides a SIEM and log management platform. The platform centralizes and analyzes event data from across complex environments. It combines log management with AI that summarizes dashboards, prioritizes risks, and automates investigation workflows. Graylog began as an open source log management project and later added SIEM capabilities on the same codebase. The company offers products including Graylog Security, Enterprise, API Security, and Open. The company is headquartered in Houston.

Products

Graylog Security: Provides threat detection, investigation, and response.
Graylog Enterprise: Provides enterprise log management, search, alerting, and reporting.
Graylog Open: Is a source-available, self-managed, free log management option.
Verascend Incident System: Turns risk-scored alerts into verified incidents.

Used for

Detecting threats across IT environments.
Investigating security incidents with assembled evidence.
Responding to incidents with guided workflows.
Proving compliance and closing audits.
Identifying and protecting Very Attacked People with automated triage.

Who it is for

Built for people covering security, IT, and audit functions.
Intended for lean security teams.
Used by teams with the engineering time to build and maintain their own log management.

From Graylog's own website, read 2026-10-23. How we build listings.

How to evaluate Log Management & Analytics

This is how the CIOPages Research Team evaluates this category. It is not an assessment of Graylog. It comes from our Log Management & Analysis buyer guide.

25%

Cost & Tiering Model at Volume

Unit of pricing (per-GB ingest, compute/SVC, credits, host, consumption) and how the bill behaves as volume grows; hot/warm/cold/frozen or archive tiers, index-free or low-cost retention tiers, rehydration cost and latency, and ingest controls or sampling to cap spend

20%

Search, Query & Analytics Power

Full-text vs. label-only vs. schema-on-read; query language depth (SPL, ES|QL/KQL, LogQL, DQL, SQL) and learning curve; performance on cold and high-cardinality data; aggregations, pattern detection, and live-tail for real-time troubleshooting

20%

Pipeline, Ingestion & OpenTelemetry

Agent footprint and collector strategy; native OpenTelemetry/OTLP ingest; parsing, enrichment, masking, routing, and reduction before storage; ability to fan data out to multiple destinations and to swap backends without re-instrumenting sources

15%

Security, Compliance & Retention

RBAC/SSO, field-level masking of sensitive data, immutable/WORM audit retention, and tamper-evident logging; SOC 2 / ISO 27001 / FedRAMP coverage and data residency; SIEM or threat-detection content if logs feed security

10%

Observability Correlation & Architecture

Whether logs sit standalone, inside an observability suite (correlated with metrics and traces), or inside the SIEM; trace-to-log pivots, unified context, and how cleanly it slots beside tooling you already run

10%

Operations, Scale & AI Assist

Self-managed vs. SaaS operational burden, multi-tenant and multi-cluster scale, ingest spikes and back-pressure handling; API/IaC coverage; and AI-assisted features such as anomaly detection, log clustering/patterns, and natural-language query

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DataSet

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