Public serverless unit rates are bound to the Essentials and Complete tiers, but total cost depends on ingestion, retention, egress, region, optional services, and deployment design. No contract commitment is inferred from these usage rates.
Microsoft Sentinel is not a per-seat subscription. Buyers must model data volume, tier, retention, query, automation, compute, and connected Azure services. Numeric offers are withheld because the current captured pricing table did not expose reliable localized amounts.
Engineering-led SOCs that want open schemas and highly customizable security analytics
Cloud and hybrid enterprises that need broad ingestion and deep historical search
Teams already using Elasticsearch and prepared to govern ECS, pipelines, detections, and data tiers
Microsoft-centric SOCs using Defender, Entra, Azure, and Microsoft 365
Multicloud and multiplatform teams that need a managed cloud SIEM
Organizations prepared to use KQL, analytics rules, automation, and security content engineering
Not for
Teams seeking a fixed all-inclusive SIEM subscription
Organizations without security-data engineering or detection-tuning capacity
Buyers requiring every advanced AI and automation feature in the lowest tier
Organizations requiring an on-premises SIEM deployment
Buyers seeking one fixed per-seat price without usage metering
Teams unable to govern cloud ingestion, retention, query, automation, and adjacent-service costs
Source check
99/100
100/100
Key features
Elastic Agent, integrations, APIs, and custom pipelines for cloud and hybrid security telemetry
ECS-based normalization with asset, identity, and threat-intelligence context
Prebuilt and custom rules, machine learning, anomaly detection, and entity analytics
Timeline investigation, KQL and ES|QL search, cases, dashboards, and threat hunting
AI Assistant, Attack Discovery, query generation, and advanced SOC workflows in supported tiers
More than 350 first- and third-party data connectors with custom integration options
ASIM normalization at ingestion and query time
Analytics rules, threat intelligence, UEBA, anomalies, and MITRE ATT&CK mapping
KQL search, entity investigation, timelines, notebooks, and proactive hunting
Incident management, automation rules, and Logic Apps-based playbooks
Cons
As-low-as unit rates do not represent a complete deployment estimate
Data ingestion, retention, egress, workflows, AI, region, and infrastructure choices can materially change total cost
Self-managed deployments transfer scaling, upgrades, resilience, and operational responsibility to the buyer
No universal starting amount because pricing is regional and consumption based
Analytics ingestion, data-lake storage and queries, automation, graph, compute, and adjacent Azure services can create separate charges
Commitment tiers require at least 31 days before reduction or exit
Category buying score
82
84Higher category-fit score
Rank
#4
#1
Context
Security & Privacy / Security Information and Event Management (SIEM) Software
Security & Privacy / Security Information and Event Management (SIEM) Software
Detection and correlation quality
83Detection content combines prebuilt rules, custom rules, machine learning, anomaly detection, and Complete-tier entity analytics, so quality scales with tuning capacity and correct ECS context rather than arriving as a turnkey sealed rule set.
84Threat intelligence, UEBA, anomalies, analytics rules, and MITRE ATT&CK mapping support detection quality, but the facts do not establish guaranteed detection coverage for every environment or content package.
Investigation and threat hunting
87Timeline, KQL, ES|QL, dashboards, and threat-hunting workflows support proactive and reactive investigation, with AI Assistant, Attack Discovery, and query generation available on supported Complete configurations for assisted SOC analysis.
87Entity investigation, timelines, notebooks, proactive hunting, and KQL search directly support analyst-led investigation and hunting, while the score stops short of 100 because operational effectiveness still depends on team skill.
Data collection and context
84Elastic Agent, integrations, APIs, and custom pipelines can collect cloud and hybrid telemetry and feed ECS-normalized security data, but the buyer must own mapping quality for custom sources, which makes the pipeline capability strong but governance-dependent.
88More than 350 connectors, custom connectors, Syslog, REST APIs, and common formats support collecting diverse security data into the platform, and ASIM normalization strengthens downstream context handling.
Response and security operations
77Cases and collaboration support incident handling on core analytics tiers, while broader automation controls and advanced AI-assisted workflows sit on Complete, so response depth tracks tier selection and configuration rather than a single uniform playbook layer.
83Incident management, automation rules, and Logic Apps-based playbooks support response operations, but the facts do not establish fully autonomous response or uniform workflow maturity across every integration.
Scale, retention, and performance
86Hot, cold, frozen, snapshot, and serverless retained-data options give buyers multiple retention and searchable-history designs, but the facts do not state retention guarantees or performance limits for every deployment mode, so the score remains below maximum.
84Analytics tiers for continuous analysis plus a data-lake tier for lower-cost historical retention let buyers scale volume and keep long-term security data without treating every table as always-on alerting storage.
Deployment, support, and total cost
69Public serverless rates start at stated per-GB ingestion and retained-data prices, but total cost also depends on egress, optional workflow and AI meters, region, and deployment design, so the purchase check is full TCO modeling rather than the headline unit rate.
65Avoids per-seat license minimums, but consumption-based pricing across compute, storage, and adjacent services creates operational complexity and budget uncertainty.
Integrations and detection content
85A broad integration and security-content ecosystem with public detection-rule content accelerates onboarding of supported sources, while custom or unsupported telemetry still requires buyer-built ECS-compatible pipelines.
89Provides a vast library of first- and third-party connectors and native integration with Defender XDR, centralizing security telemetry across multicloud and on-premises logs.
These are the stored dimension rationales returned with each score. They explain the buyer conditions behind the gap without speculating about hidden model reasoning.
Response and security operations
6 pts
Elastic Security · 77/100
Cases and collaboration support incident handling on core analytics tiers, while broader automation controls and advanced AI-assisted workflows sit on Complete, so response depth tracks tier selection and configuration rather than a single uniform playbook layer.
Microsoft Sentinel · 83/100
Incident management, automation rules, and Logic Apps-based playbooks support response operations, but the facts do not establish fully autonomous response or uniform workflow maturity across every integration.
Data collection and context
4 pts
Elastic Security · 84/100
Elastic Agent, integrations, APIs, and custom pipelines can collect cloud and hybrid telemetry and feed ECS-normalized security data, but the buyer must own mapping quality for custom sources, which makes the pipeline capability strong but governance-dependent.
Microsoft Sentinel · 88/100
More than 350 connectors, custom connectors, Syslog, REST APIs, and common formats support collecting diverse security data into the platform, and ASIM normalization strengthens downstream context handling.
Deployment, support, and total cost
4 pts
Elastic Security · 69/100
Public serverless rates start at stated per-GB ingestion and retained-data prices, but total cost also depends on egress, optional workflow and AI meters, region, and deployment design, so the purchase check is full TCO modeling rather than the headline unit rate.
Microsoft Sentinel · 65/100
Avoids per-seat license minimums, but consumption-based pricing across compute, storage, and adjacent services creates operational complexity and budget uncertainty.
Research basis
Research basis
This page uses stored product facts, official evidence, and category scoring rationales. It is not an account-based hands-on test, and third-party user ratings are not folded into the category buying score.
Elastic Security
Fact confidence: 99% · Fact checked: 2026-08-10
Microsoft Sentinel
Fact confidence: 100% · Fact checked: 2026-08-10
More tools
Security Information and Event Management (SIEM) Software
Add more tools from the same subcategory to this comparison. The page keeps up to 6 tools.
Microsoft Sentinel is a cloud-native SIEM and security operations platform for collecting, detecting, investigating, hunting, and responding across Microsoft and third-party environments.
Google Security Operations is a cloud-native SIEM and SOAR platform that ingests and normalizes security telemetry, detects threats, supports investigation and hunting, and automates response workflows.
Elastic Security is a unified security operations platform that provides SIEM, threat detection, investigation, hunting, case management, and response across cloud-hosted or self-managed Elastic deployments.
IBM QRadar Suite Software is an on-premises enterprise security operations package that combines QRadar SIEM entitlements with case management, federated investigation, threat intelligence, and separately deployable response and detection products.
LogRhythm SIEM is Exabeam's self-hosted security information and event management platform for collecting, normalizing, detecting, investigating, reporting, and responding across customer-managed environments.
Exabeam New-Scale SIEM is a cloud-native security information and event management product for collecting, normalizing, searching, detecting, investigating, and responding across enterprise security data.