Top 10 Splunk Competitors in 2025

What Is Splunk? 

Splunk is a software platform for searching, monitoring, and analyzing machine-generated data via a web interface. Splunk aims to help organizations manage large datasets by indexing and correlating real-time data in a searchable repository, producing graphs, alerts, dashboards, and visualizations. 

With its scalability, Splunk accommodates varying data inputs from many sources, including applications, servers, security devices, and networks. The ability to automate data collection and analysis makes Splunk a solution in environments that require constant data surveillance and quick reaction times. 

It is used in industries such as IT, security, and business analytics, helping organizations harness their data for performance monitoring, security improvement, and operational efficiency.

This is part of a series of articles about Splunk SIEM

Key Splunk Limitations 

While Splunk offers robust capabilities for handling and analyzing machine data, it also comes with several limitations that organizations should consider. These limitations were reported by users on the G2 platform:

• High licensing costs: Splunk’s pricing model is expensive, particularly for large enterprises. Costs increase significantly when multiple users need access, and its licensing can be difficult to manage and sell.
• Complex licensing model: The licensing structure is not straightforward, creating challenges for vendors and partners, especially after its acquisition by Cisco.
• Resource-heavy queries: Complex searches can consume significant system resources, leading to performance degradation and a need for careful infrastructure planning.
• Steep learning curve: Fully utilizing Splunk’s capabilities often requires in-depth knowledge of its proprietary search language (SPL), making onboarding difficult for new users.
• Limited APM support: Splunk does not currently offer built-in support for application performance monitoring, limiting its use in certain observability scenarios.
• UI and usability issues: The management interface can be hard to navigate for new users. The web application is slower than the desktop version and may crash under load.
• Integration challenges: Some integration capabilities with other technologies have been reduced or limited in recent versions.
• Uncertainty post-acquisition: Since being acquired by Cisco, aspects like pricing policy and long-term strategy remain unclear, which introduces risk for current and potential users.

In light of these limitations, many organizations are considering competitors.

10 Notable Splunk Competitors

The following table summarizes the Splunk competitors, their deployment models, and what they provide that Splunk doesn’t. Below we review each of the competitors in more detail.

Solution	Deployment Model	Why Choose Instead of Splunk
Exabeam	Cloud, on-prem, hybrid	Advanced behavioral analytics and UEBA; faster deployment on Cloud
Microsoft Sentinel	SaaS (Azure-native)	Cloud-native scalability; built‑in AI/ML and Microsoft threat intel
IBM QRadar	On‑prem, cloud, appliance	Unified SIEM/SOAR/EDR in one; EPS‑based pricing
Elastic Security	Self‑managed (Elastic Stack) or Elastic Cloud (hosted/serverless)	Full‑text search over big data; open model; scalable pricing
SolarWinds SEM	Virtual appliance (on‑prem)	Budget-friendly; simple licensing; compliance‑focused
Fortinet FortiSIEM	On‑prem or managed appliance	IT/OT coverage with built-in CMDB; embedded FortiAI for summaries
Datadog Cloud SIEM	SaaS (on Datadog platform)	Combines observability and security; event‑level visibility and context
Sumo Logic Cloud SIEM	SaaS	Native cloud SIEM with signal clustering, ATT&CK mapping
Graylog Security	Self‑hosted or cloud	Cost‑effective open architecture; MITRE ATT&CK mapping and SOAR
Logpoint SIEM	On‑prem, cloud, hybrid	Strong compliance support and standardized data taxonomy; easy ATT&CK alignment

1. Exabeam

Exabeam is a next-generation SIEM platform built to modernize security operations with behavioral analytics, automation, and AI. It was designed to overcome many of Splunk’s challenges around cost, complexity, and usability, offering a more efficient way to detect, investigate, and respond to threats. Exabeam supports cloud, on-premises, and hybrid deployments, making it a flexible choice for organizations of all sizes.

Key Features Include:

• Behavioral analytics (UEBA): Uses machine learning to baseline normal activity for users, devices, and entities, then flags anomalies that may indicate credential abuse, insider threats, or advanced attacks.
• Automated investigations: Exabeam Smart Timelines™ automatically stitch together related events from across systems, reducing the need for manual log correlation and accelerating response.
• AI-driven assistance: Exabeam Nova, a system of AI agents, helps automate tasks such as detection engineering, threat hunting, and executive-level security reporting.
• Flexible data ingestion: Supports ingestion from virtually any log source, with connectors for threat intelligence providers, EDR, cloud platforms, and more.
• Risk-based prioritization: Combines IOCs and behavioral anomalies into a risk score, allowing analysts to focus on the threats most likely to cause impact.

Splunk use cases you can replace with Exabeam:

• Centralized log management and threat detection across cloud and hybrid infrastructures
• Advanced detection of insider threats and credential misuse using UEBA
• Automated investigations that reduce alert fatigue and SOC workload
• Risk-scored alerts that prioritize the most critical threats
• Executive reporting that ties security outcomes directly to business priorities

LogRhythm (On-Premises Option from Exabeam)

LogRhythm is a long-established SIEM platform often chosen by organizations seeking a robust on-premises solution. It combines log management, machine analytics, and automated workflows to help security teams detect and respond to threats quickly. LogRhythm’s strength lies in its ability to operate in highly regulated or air-gapped environments where cloud deployments may not be viable.

Key features include:

• On-premises focus: Purpose-built for organizations that need local data control due to compliance, sovereignty, or operational requirements.
• Comprehensive threat lifecycle management: Provides end-to-end visibility across collection, detection, investigation, and mitigation.
• Integrated SOAR: Automates response through playbooks that can quarantine hosts, disable accounts, or escalate tickets without manual intervention.
• Behavioral analytics: Detects anomalies by comparing real-time activity against baselines, improving detection of insider threats and advanced attacks.
• Compliance reporting: Comes with out-of-the-box content packs for PCI DSS, HIPAA, GDPR, and other regulatory frameworks.
  

Splunk use cases you can replace with LogRhythm:

• On-premises log management for regulated industries (finance, healthcare, government)
• Automated compliance reporting and audit preparation
• Threat detection and response in air-gapped or private data center environments
• Cost-effective SIEM with integrated SOAR for mid-sized enterprises
• Behavioral analytics-driven anomaly detection without reliance on complex queries

2. Microsoft Sentinel

Microsoft Sentinel is a cloud-native SIEM and SOAR platform built on Azure, providing threat detection, investigation, and response. It collects and correlates data from various sources—on-premises, multi-cloud, and hybrid environments—and enriches analysis with Microsoft’s threat intelligence and artificial intelligence. 

Key features include:

• Cloud-native SIEM and SOAR: Scales automatically and reduces infrastructure management by operating in the cloud.
• Integrated threat intelligence: Uses Microsoft’s global threat intelligence and allows custom threat intelligence integration.
• Data collection at scale: Supports out-of-the-box and custom connectors for collecting data from Microsoft and non-Microsoft sources.
• Advanced threat detection: Uses analytics rules and machine learning to detect anomalies and correlate events into actionable incidents.
• MITRE ATT&CK mapping: Visualizes threats using tactics and techniques from the MITRE ATT&CK framework.

Splunk use cases you can replace with Microsoft Sentinel: 

• Centralized log ingestion and correlation across Microsoft 365, Azure, AWS, and on-prem systems
• Threat detection using anomaly-based and rule-based analytics
• MITRE ATT&CK-based investigation and visualization of incidents
• Automated incident response with playbooks using Logic Apps
• Compliance monitoring and reporting aligned with standards like ISO 27001 and NIST

Source: Microsoft 

3. IBM QRadar

IBM QRadar is a threat detection and response platform intended to accelerate security operations across the incident lifecycle. It brings together SIEM, SOAR, and endpoint detection and response (EDR) capabilities. It aims to improve analyst productivity and help security teams respond to threats faster.

Key features include:

• Unified security suite: Combines SIEM, SOAR, and EDR with integrated workflows.
• AI-powered threat detection: Uses artificial intelligence, behavior analytics, and threat intelligence to provide prioritized alerts.
• QRadar SIEM: Delivers threat detection and correlation through analysis of network and user activity.
• QRadar SOAR: Automates incident response playbooks to enforce consistent processes.
• QRadar EDR: Detects and responds to zero-day threats using machine learning models and external OS monitoring.

Splunk use cases you can replace with IBM QRadar: 

• Real-time log and event correlation from diverse enterprise systems
• Behavior analytics-driven detection of insider threats
• Incident investigation workflows with integrated threat intelligence
• Automated incident response via SOAR playbooks
• Threat hunting using network and user activity data

Source: IBM

4. Elastic Security

Elastic Security is a threat detection and response solution built on the ElasticSearch AI platform. It combines SIEM, threat research, and AI-driven analytics to help security operations teams detect, investigate, and respond to threats. It is designed to support large-scale data analysis across cloud and on-premises environments.

Key features include:

• AI-driven SIEM: Uses AI to power analytics and deliver rapid threat detection.
• Continuous monitoring: Ingests and normalizes diverse data sources—from cloud, user, and network telemetry.
• Automated threat protection: Detects attacks using behavior analytics, anomaly detection, and coverage mapped to MITRE ATT\&CK.
• AI-enhanced SecOps: Speeds up detection and response with contextual AI insights and workflow acceleration.
• Threat hunting: Enables threat discovery with machine learning and data analysis enriched by threat intelligence.

Splunk use cases you can replace with Elastic Security: 

• Scalable log ingestion and full-text search over large datasets
• Threat detection using prebuilt detection rules and machine learning jobs
• Visual threat investigation through Kibana dashboards
• Endpoint monitoring and data collection with Elastic Agent
• Threat hunting and investigation with pivotable queries across timelines

Source: Elastic

5. SolarWinds SIEM

SolarWinds Security Event Manager (SEM) is marketed as an affordable SIEM tool to help organizations strengthen their security posture and meet compliance requirements. It centralizes and correlates log data from across the network, providing threat detection and simplified reporting. 

Key features include:

• Centralized log management: Collects and normalizes log data from various sources using built-in connectors.
• Real-time threat detection: Correlates events in real time to uncover policy violations and suspicious activity.
• Compliance reporting: Includes pre-built templates for standards like PCI DSS, HIPAA, and SOX.
• Automated incident response: Triggers predefined responses to detected threats, reducing manual workload.
• Cyber threat intelligence integration: Enhances visibility with threat intelligence feeds that help detect known malicious activity.

Splunk use cases you can replace with SolarWinds: 

• Log collection from firewalls, servers, and network devices
• Real-time event correlation for security and compliance
• Basic threat detection and alerting on suspicious patterns
• Compliance audit reporting for standards like PCI and HIPAA
• Automation of alerts and responses using predefined actions

Source: SolarWinds 

6. Fortinet FortiSIEM

Fortinet FortiSIEM is a security operations platform that unifies threat detection, incident response, and compliance. Designed to serve IT and OT environments, it combines analytics, asset discovery, and a configuration management database (CMDB) to provide visibility and detection. 

Key features include:

• Built-in IT/OT CMDB: Automatically discovers and continuously monitors assets.
• Advanced threat detection: Uses user and entity behavior analytics (UEBA), correlation rules, and machine learning to detect IT and OT threats.
• FortiAI integration: Embedded generative AI helps interpret logs, summarize incidents, and recommend remediation actions using natural language prompts.
• Endpoint forensics: Integrates with OSquery for endpoint visibility and forensic analysis.
• Visualization and investigation tools: Link graph technology shows relationships among users, assets, and events.

Splunk use cases you can replace with FortiSIEM: 

• Correlation of security data from IT and OT environments
• Threat detection using UEBA and rule-based analytics
• Asset inventory and automatic discovery of networked devices
• Incident response enriched with AI-generated summaries
• Visual investigation of entity relationships using graph views

Source: Fortinet 

7. Datadog

Datadog Cloud SIEM is a cloud-native security solution that merges threat detection with observability context to accelerate security investigations and response. Built on Datadog’s log management platform, it enables collaboration across development, security, and operations teams by centralizing security data and insights. 

Key features include:

• Threat detection: Detects and correlates suspicious activity using detection rules aligned with the MITRE ATT&CK framework.
• Unified security and observability: Links operational and security data to provide full-stack context for investigation and root cause analysis.
• Log analysis: Uses Log Explorer and Workspaces to visualize security data as charts or tables.
• Out-of-the-box content: Speeds deployment with preconfigured detection rules, dashboards, visualizations, and workflows.
• Rapid onboarding: Onboards new data sources quickly through integrations and observability pipelines.

Splunk use cases you can replace with Datadog: 

• Correlation of security logs with observability metrics for root cause analysis
• MITRE ATT&CK-based detection rule implementation
• Real-time visualization of logs in dashboards and charts
• Centralized alerting and incident workflows across DevSecOps teams
• Log ingestion and parsing from cloud-native sources and containers

Source: Datadog 

8. Sumo Logic

Sumo Logic Cloud SIEM is a cloud-native security solution to simplify threat detection, investigation, and response. It helps SOC teams reduce alert fatigue, correlate high-risk threats, and accelerate investigations by combining analytics, behavioral insights, and automation. 

Key features include:

• Threat detection: Parses and normalizes structured and unstructured data to detect threats and reduce noise.
• Insight engine and signal clustering: Automatically groups related security signals and elevates correlated activity into prioritized insights.
• MITRE ATT\&CK coverage explorer: Maps detection rules to MITRE ATT&CK to highlight detection strengths, uncover coverage gaps, and guide security strategy.
• UEBA (user and entity behavior analytics): Detects anomalies by comparing user and entity behavior to established baselines.
• Entity relationship graph: Visualizes connections among entities and related activities, helping analysts understand the scope of an incident.

Splunk use cases you can replace with Sumo Logic: 

• Centralized SIEM for cloud-native and hybrid environments
• Detection and correlation of threats across structured and unstructured logs
• MITRE ATT&CK mapping for visibility into detection coverage
• Alert deduplication and signal clustering to reduce analyst fatigue
• Threat investigation with entity graphs and contextual analysis

Source: Sumo Logic 

9. Graylog

Graylog Security is a SIEM and threat detection, investigation, and response (TDIR) platform intended to meet the needs of security operations centers. Built on the Graylog Platform, it provides threat management with integrated SOAR capabilities and curated security content. 

Key features include:

• End-to-end TDIR platform: Centralizes threat detection, investigation, and response with built-in automation.
• Curated detection content: Provides out-of-the-box coverage through Graylog Illuminate content packs, delivering prebuilt alerts, dashboards, and event definitions.
• MITRE ATT&CK mapping: Automatically maps detections to the MITRE ATT&CK framework to visualize active threat coverage and identify gaps.
• Aligned threat coverage: Tailors detections to the organization’s risk profile.
• Integrated data management: Offers native data tiering, routing, and archiving.

Splunk use cases you can replace with Graylog: 

• Log aggregation and normalization from diverse IT sources
• Threat detection using curated detection packs and correlation rules
• MITRE ATT&CK mapping for detection coverage analysis
• Automation of response actions using built-in SOAR capabilities
• Security monitoring with out-of-the-box dashboards and alerts

Source: Graylog 

10. Logpoint

Logpoint SIEM is a security analytics platform that unifies data ingestion, normalization, detection, and compliance. It helps analysts to detect threats faster and respond with compliance support and flexible deployment options.

Key features include:

• Centralized data monitoring: Ingests logs and events from any device, application, or endpoint to provide a unified view of the infrastructure.
• Normalized data taxonomy: Translates collected data into a standard format.
• Contextual enrichment: Adds threat intelligence, geo-location, and LDAP data to improve detection accuracy.
• MITRE ATT&CK mapping: Aligns alerts and behaviors to the MITRE framework to simplify threat analysis and response.
• Out-of-the-box compliance support: Comes with prebuilt dashboards and reports to meet regulatory requirements such as GDPR, NIS2, and GPG13.

Splunk use cases you can replace with Logpoint: 

• Alerting and visualization via prebuilt dashboards and reports
• Log ingestion and normalization across multi-vendor environments
• Detection of security events mapped to MITRE ATT&CK techniques
• Threat context enrichment using geolocation and external threat feeds
• Compliance reporting for GDPR, NIS2, and other regulations

Source: Logpoint

Conclusion

Splunk remains a popular option for analyzing machine data, but it’s important to weigh its limitations alongside newer or more specialized alternatives. As the SIEM and observability landscape continues to evolve, organizations have a growing range of tools to choose from—many of which emphasize cloud-native architectures, integrated automation, and improved usability. Selecting the right platform depends on operational needs, including scalability, budget, integration capabilities, and response speed.