software
PagerDuty vs Splunk 2026: Incident Response vs Log Analytics
PagerDuty is an incident response and on-call management platform focused on alerting and team coordination, while Splunk is a data analytics and monitoring platform that ingests, indexes, and analyzes machine-generated data. They serve different primary functions but increasingly overlap in observability workflows.
P
PagerDuty
Incident response and on-call management platform for alert orchestration and team coordination.
DevOps teams, SREs, and operations centers needing rapid incident response coordination and on-call management without custom monitoring complexity.
Score63%
VS
Splunk
Data analytics platform for ingesting, indexing, and analyzing machine-generated data from applications, infrastructure, and security systems.
Enterprises needing comprehensive log analysis, security analytics, compliance monitoring, and deep operational intelligence across distributed systems.
Score63%
Quick Answer
AI SummaryPagerDuty is an incident response and on-call management platform focused on alerting and team coordination, while Splunk is a data analytics and monitoring platform that ingests, indexes, and analyzes machine-generated data. They serve different primary functions but increasingly overlap in observability workflows.
Our Verdict
AI-assistedChoose PagerDuty if your primary need is managing on-call schedules, routing alerts efficiently to the right teams, and reducing response times—it excels at orchestration and costs less to implement. Choose Splunk if you need deep log analysis, complex data correlation, security analytics, and root cause investigation across massive data volumes—it's the better platform for forensics and advanced observability but requires higher investment and longer setup.
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P
PagerDuty
9.2/10
Splunk
5.8/10
P
Choose PagerDuty if
Best pickDevOps teams, SREs, and operations centers needing rapid incident response coordination and on-call management without custom monitoring complexity.
Choose Splunk if
Enterprises needing comprehensive log analysis, security analytics, compliance monitoring, and deep operational intelligence across distributed systems.
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Key Differences at a Glance
- Primary Function:Incident response & on-call management vs Data analytics & log aggregation
- Starting Price (Annual):✓ PagerDuty wins($1,500 (5 users) vs $4,500 (500GB/day ingest))
- Data Ingestion Capacity (Standard):✓ Splunk wins(GB/day: 500GB-5TB+ vs Alerts per minute: 10,000+)
Key Facts & Figures
98 numeric metrics compared
| Metric | PagerDuty | Splunk | Ratio |
|---|---|---|---|
| Starting Monthly Cost per User(USD) | $49 | — | — |
| Available Integrations(integrations) | 600+ | — | — |
| Free Trial Period(days) | 14 days | — | — |
| Uptime SLA Guarantee(percentage) | 99.99% | — | — |
| Estimated Global Market Share(percentage) | 28% | — | — |
| Base Monthly Cost Per User(USD) | $49 | — | — |
| Free Tier User Limit(users) | 3 users | — | — |
| Data Source Integrations(count) | 200+ integrations | — | — |
| Mean Time to Response (MTTR) Improvement(percent) | 58% faster | — | — |
| Alert Fatigue Reduction(percent) | 60% via deduplication | — | — |
| Customer Retention Rate(percent) | 96% | — | — |
| Native Monitoring Capabilities(integrations) | 400+ via integrations | — | — |
| Alert Grouping Reduction(%) | 75% alert noise reduction | — | — |
| MTTR Improvement vs Manual(%) | 87% faster | — | — |
| Typical Setup Time(hours) | 8-16 hours | — | — |
| Founding Year | 2010 | — | — |
| Native Integrations Available(integrations) | 600+ | — | — |
| Base Monthly Cost (10 users)(USD) | $490/month | — | — |
| Cost at 100 Users(USD/month) | $4,900/month | — | — |
| Average Incident Resolution Time Improvement(percent) | 35% faster (reported by customers) | — | — |
| Fortune 500 Adoption Rate(percent) | 70%+ | — | — |
| Base Annual Cost(USD) | $1,449 | $2,400 | |
| Additional Data Ingestion Cost(USD per 10GB/day) | N/A - not data-focused | $250-350 | — |
| Number of Integrations(count) | 600+ | 900+ | |
| Time to Incident Creation from Alert(seconds) | <60 seconds | Not applicable (generates alerts) | — |
| Standard Data Retention(days) | N/A - incident focused | 30-365 days | — |
| Base Monthly Cost (5 Users, Annual Commitment)(USD/month) | $1,495 | — | — |
| Native Integrations(count) | 5,000+ | — | — |
| Mobile Push Notification Latency(seconds) | <2 seconds | — | — |
| Communication Channels Supported(count) | 6 channels | — | — |
| Atlassian Bundle Discount(percent) | 0% | — | — |
| Average Onboarding Time(days) | 5-7 days | — | — |
| Founded Year(year) | 2009 | — | — |
| Available Integrations(count) | 500+ | — | — |
| Base Monthly Pricing(USD) | $49/user | — | — |
| Customers (Approximate)(count) | 10,000+ | — | — |
| Starting Annual Cost(USD) | $1,500 | $4,500 | |
| Cost per 100 Users (Annual)(USD) | $15,000-$25,000 | $36,000-$180,000 | |
| Data Ingestion Capacity (Standard Plan)(GB/day) | Alerts: unlimited routing | 500GB | — |
| Average Implementation Timeline(weeks) | 3 | 8 | |
| Number of Pre-built Integrations(count) | 700+ | 600+ | |
| Maximum Alerts Per Minute Capacity(alerts/min) | 10,000+ | Limited by ingestion | — |
| Base Monthly Cost (100GB/day)(USD) | $3,500-$5,500 | $3,500-$5,500 | |
| Annual TCO (1TB/day ingestion)(USD) | $450,000-$750,000 | $450,000-$750,000 | |
| Deployment Time(seconds) | 21-30 days | 21-30 days | |
| Default Data Retention(days) | 30 days included | 30 days included | |
| Query Performance (5TB dataset)(seconds) | 8-12 seconds | 8-12 seconds | |
| Third-party Integrations(count) | 2,000+ apps | 2,000+ apps | |
| Gartner SIEM Market Share(percent) | 28% (2024) | 28% (2024) | |
| Machine Learning Models(count) | 50+ algorithms | 50+ algorithms | |
| Mean Time to Detection (MTTD)(minutes) | 15-60 minutes (depends on alert configuration) | 15-60 minutes (depends on alert configuration) | |
| Starting Annual Cost (single user/endpoint)(USD) | $3,000-6,000 | $3,000-6,000 | |
| Pre-built Integrations/Apps(count) | 800+ apps in Splunkbase | 800+ apps in Splunkbase | |
| Agent Size/System Footprint(MB) | Heavy (varies, 500MB+) | Heavy (varies, 500MB+) | |
| Base Annual Cost (Small Deployment)(USD) | $3,000 - $5,000 | $3,000 - $5,000 | |
| Per-Gigabyte Ingestion Cost(USD per GB per day) | $0.80 - $1.50 | $0.80 - $1.50 | |
| Setup Time to Production(minutes) | 4-8 (managed cloud) | 4-8 (managed cloud) | |
| Query Response Time (1B records)(milliseconds) | 100-300ms | 100-300ms | |
| Built-in Compliance Certifications(count) | 6 (HIPAA, SOC2, PCI-DSS, FedRAMP, GDPR, ISO27001) | 6 (HIPAA, SOC2, PCI-DSS, FedRAMP, GDPR, ISO27001) | |
| Machine Learning Use Cases Included(count) | 15+ (threat detection, predictive analytics, correlation, clustering) | 15+ (threat detection, predictive analytics, correlation, clustering) | |
| Maximum Cluster Nodes(nodes) | Unlimited (license-dependent) | Unlimited (license-dependent) | |
| Community Support Response Time(hours) | 1 (24/7 enterprise SLA) | 1 (24/7 enterprise SLA) | |
| Average Cost per GB Ingested(USD) | $1.50 | $1.50 | |
| Typical Deployment Timeline(weeks) | 7 weeks | 7 weeks | |
| Default Data Retention Period(months) | 120 months (10 years) | 120 months (10 years) | |
| Out-of-Box Integrations(count) | 700+ integrations | 700+ integrations | |
| APM Real-Time Metric Resolution(seconds) | 10-30 seconds | 10-30 seconds | |
| Uptime SLA Guarantee(percent) | 99.95% | 99.95% | |
| Learning Curve (Time to Productivity)(weeks) | 4-6 weeks | 4-6 weeks | |
| Monthly Cost (100GB/day ingestion)(USD) | $10,000-25,000 | $10,000-25,000 | |
| Implementation Timeline(weeks) | 14-42 days | 14-42 days | |
| Time-to-First-Alert(minutes) | 15-30 minutes | 15-30 minutes | |
| Default Data Retention (included in pricing)(months) | 12 months | 12 months | |
| SIEM Compliance Modules (pre-built)(count) | 12 (HIPAA, PCI, SOC2, NIST) | 12 (HIPAA, PCI, SOC2, NIST) | |
| Enterprise Customers(millions) | 10,000+ (2024) | 10,000+ (2024) | |
| Base Monthly Cost (Single User Cloud)(USD) | $4,500+ (minimum commitment) | $4,500+ (minimum commitment) | |
| Annual Cost (1GB/day Log Ingestion)(USD) | $54,000-$108,000 | $54,000-$108,000 | |
| Log Query Response Time(milliseconds) | <100 | <100 | |
| Event Ingestion Rate (Single Indexer)(events/sec) | 10,000+ | 10,000+ | |
| Native Data Source Integrations(count) | 400+ | 400+ | |
| Built-in Machine Learning Algorithms(count) | 50+ | 50+ | |
| Minimum RAM Requirement (Self-Hosted)(GB) | 8+ | 8+ | |
| Base Monthly Pricing (1GB/day ingestion)(USD) | $1,500-$2,000 | $1,500-$2,000 | |
| Query Response Time (1GB dataset)(milliseconds) | 2,000-5,000ms | 2,000-5,000ms | |
| SIEM Use Cases Supported(count) | 400+ built-in detections | 400+ built-in detections | |
| Pre-built Integrations(count) | 300+ | 300+ | |
| Base License Cost (Annual)(USD) | $5,000 minimum | $5,000 minimum | |
| Typical Enterprise Implementation Cost(USD) | $50,000-$200,000 | $50,000-$200,000 | |
| Data Sources Supported(integrations) | 150+ (broader enterprise data ecosystem) | 150+ (broader enterprise data ecosystem) | |
| Average Search Query Time (1GB dataset)(seconds) | 1-5 seconds | 1-5 seconds | |
| Built-in Machine Learning Models(count) | 20+ (anomaly detection, forecasting, UEBA) | 20+ (anomaly detection, forecasting, UEBA) | |
| Typical Deployment Time(minutes) | 8-16 weeks | 8-16 weeks | |
| GitHub Stars (Community Adoption)(stars) | 2,500+ (proprietary, less open) | 2,500+ (proprietary, less open) | |
| Minimum Monthly Commitment(USD) | $3,600 ($120/day minimum) | $3,600 ($120/day minimum) | |
| Initial Deployment Time(minutes) | 2,880 (4-8 weeks average) | 2,880 (4-8 weeks average) | |
| Log Ingestion at $10k/Month Spend(GB per day) | ~200 | ~200 | |
| Default Metrics Retention(days) | 30 (upgradeable to unlimited) | 30 (upgradeable to unlimited) | |
| Enterprise Customer Count (2025)(organizations) | 12,000 | 12,000 |
Sourced from publicly available data ·
Key Differences
7 attributes compared head-to-head
P
3PagerDutyPagerDuty leads2 ties
PagerDuty
Attribute
Splunk
- Incident response & on-call managementPrimary FunctionData analytics & log aggregation
- $1,500 (5 users)(winner)Starting Price (Annual)$4,500 (500GB/day ingest)
- Alerts per minute: 10,000+Data Ingestion Capacity (Standard)GB/day: 500GB-5TB+(winner)
- Primary: Orchestration & routingMean Time to Resolution (MTTR) FocusPrimary: Root cause analysis
- 700+ integrations (monitoring tools)(winner)Integration Ecosystem600+ apps & add-ons
- 2-4 weeks(winner)Typical Implementation Time4-12 weeks
- Event correlation & anomaly detection (basic)Machine Learning CapabilitiesAdvanced ML for outlier detection & forecasting(winner)
- Primary Function
PagerDuty
Incident response & on-call management
Splunk
Data analytics & log aggregation
- Starting Price (Annual)
PagerDuty
$1,500 (5 users)(winner)
Splunk
$4,500 (500GB/day ingest)
- Data Ingestion Capacity (Standard)
PagerDuty
Alerts per minute: 10,000+
Splunk
GB/day: 500GB-5TB+(winner)
- Mean Time to Resolution (MTTR) Focus
PagerDuty
Primary: Orchestration & routing
Splunk
Primary: Root cause analysis
- Integration Ecosystem
PagerDuty
700+ integrations (monitoring tools)(winner)
Splunk
600+ apps & add-ons
- Typical Implementation Time
PagerDuty
2-4 weeks(winner)
Splunk
4-12 weeks
- Machine Learning Capabilities
PagerDuty
Event correlation & anomaly detection (basic)
Splunk
Advanced ML for outlier detection & forecasting(winner)
Full Comparison
| Attribute | PagerDuty | Splunk |
|---|---|---|
| Starting Monthly Cost per User(USD) | $49 | — |
| Free Trial Period(days) | 14 days | — |
| Base Monthly Cost Per User(USD) | $49 | — |
| Free Tier User Limit(users) | 3 users | — |
| Base Monthly Cost (10 users)(USD) | $490/month | — |
Show 21 more attributesCost at 100 Users(USD/month) $4,900/month — Base Annual Cost(USD) $1,449 $2,400 Additional Data Ingestion Cost(USD per 10GB/day) N/A - not data-focused $250-350 Base Monthly Cost (5 Users, Annual Commitment)(USD/month) $1,495 — Atlassian Bundle Discount(percent) 0% — Base Monthly Pricing(USD) $49/user — Starting Annual Cost(USD) $1,500 $4,500 Cost per 100 Users (Annual)(USD) $15,000-$25,000 $36,000-$180,000 Base Monthly Cost (100GB/day)(USD) $3,500-$5,500 — Annual TCO (1TB/day ingestion)(USD) $450,000-$750,000 — Starting Annual Cost (single user/endpoint)(USD) $3,000-6,000 — Base Annual Cost (Small Deployment)(USD) $3,000 - $5,000 — Per-Gigabyte Ingestion Cost(USD per GB per day) $0.80 - $1.50 — Average Cost per GB Ingested(USD) $1.50 — Monthly Cost (100GB/day ingestion)(USD) $10,000-25,000 — Base Monthly Cost (Single User Cloud)(USD) $4,500+ (minimum commitment) — Annual Cost (1GB/day Log Ingestion)(USD) $54,000-$108,000 — Base Monthly Pricing (1GB/day ingestion)(USD) $1,500-$2,000 — Base License Cost (Annual)(USD) $5,000 minimum — Typical Enterprise Implementation Cost(USD) $50,000-$200,000 — Minimum Monthly Commitment(USD) $3,600 ($120/day minimum) — | ||
| Available Integrations(integrations) | 600+ | — |
| Available Integrations(count) | 500+ | — |
| Pre-built Integrations/Apps(count) | 800+ apps in Splunkbase | — |
| Mobile App Rating(quality level) | 4.8/5 | — |
| Jira Integration Depth | API-based integration | — |
| Data Source Integrations(count) | 200+ integrations | — |
| Jira Sync Capability | One-way basic plugin sync | — |
| Multi-tenant Deployment Options | Cloud, hybrid, self-hosted (enterprise) | — |
| Open-Source Self-Hosted Availability(null) | Enterprise tier only | — |
| Average Implementation Timeline(weeks) | 3(winner) | 8 |
| Agent Size/System Footprint(MB) | Heavy (varies, 500MB+) | — |
| Setup Time to Production(minutes) | 4-8 (managed cloud) | — |
Show 1 more attributeImplementation Timeline(weeks) 14-42 days — | ||
| Uptime SLA Guarantee(percentage) | 99.99% | — |
| Uptime SLA Guarantee(percent) | 99.95% | — |
| Estimated Global Market Share(percentage) | 28% | — |
| Customers (Approximate)(count) | 10,000+ | — |
| Gartner SIEM Market Share(percent) | 28% (2024) | — |
| Enterprise Customer Count (2025)(organizations) | 12,000 | — |
| Mean Time to Response (MTTR) Improvement(percent) | 58% faster | — |
| Alert Fatigue Reduction(percent) | 60% via deduplication | — |
| Alert Grouping Reduction(%) | 75% alert noise reduction | — |
| MTTR Improvement vs Manual(%) | 87% faster | — |
| Average Incident Resolution Time Improvement(percent) | 35% faster (reported by customers) | — |
Show 16 more attributesTime to Incident Creation from Alert(seconds) <60 seconds Not applicable (generates alerts) Mobile Push Notification Latency(seconds) <2 seconds — Data Ingestion Capacity (Standard Plan)(GB/day) Alerts: unlimited routing 500GB Maximum Alerts Per Minute Capacity(alerts/min) 10,000+ Limited by ingestion Deployment Time(seconds) 21-30 days — Default Data Retention(days) 30 days included — Query Performance (5TB dataset)(seconds) 8-12 seconds — Query Response Time (1B records)(milliseconds) 100-300ms — APM Real-Time Metric Resolution(seconds) 10-30 seconds — Time-to-First-Alert(minutes) 15-30 minutes — Log Query Response Time(milliseconds) <100 — Event Ingestion Rate (Single Indexer)(events/sec) 10,000+ — Query Response Time (1GB dataset)(milliseconds) 2,000-5,000ms — Average Search Query Time (1GB dataset)(seconds) 1-5 seconds — Typical Deployment Time(minutes) 8-16 weeks — Log Ingestion at $10k/Month Spend(GB per day) ~200 — | ||
| Customer Retention Rate(percent) | 96% | — |
| Native Monitoring Capabilities(integrations) | 400+ via integrations | — |
| Log Retention Standard Plan(days) | Not included | — |
| Native APM Included | No (integration only) | — |
| On-Call Scheduling Features(null) | Native, advanced rotation policies | — |
| Native Integrations Available(integrations) | 600+ | — |
Show 16 more attributesMobile App Incident Management(availability) Full (scheduling, ack, resolve on mobile) Limited (dashboards only) Standard Data Retention(days) N/A - incident focused 30-365 days Communication Channels Supported(count) 6 channels — On-Call Scheduling Complexity Advanced (rotations, overrides, patterns) — Post-Incident Review Capability Basic manual reviews — Built-in Collaboration Space Chat integration required — Out-of-Box Integrations(count) 700+ integrations — Default Data Retention (included in pricing)(months) 12 months — Native Data Source Integrations(count) 400+ — Built-in Machine Learning Algorithms(count) 50+ — APM Distributed Tracing(languages supported) Limited (add-on required) — Pre-built Integrations(count) 300+ — Data Sources Supported(integrations) 150+ (broader enterprise data ecosystem) — Full-Text Log Indexing Yes (native) — Built-in Machine Learning Models(count) 20+ (anomaly detection, forecasting, UEBA) — Native APM Capability Requires add-on license ($X additional) — | ||
| Typical Setup Time(hours) | 8-16 hours | — |
| Founding Year | 2010 | — |
| Enterprise SSO (SAML/OAuth) | Yes | — |
| Built-in Compliance Certifications(count) | 6 (HIPAA, SOC2, PCI-DSS, FedRAMP, GDPR, ISO27001) | — |
| SIEM Compliance Modules (pre-built)(count) | 12 (HIPAA, PCI, SOC2, NIST) | — |
| Enterprise Security Features(count) | Enterprise Security module, threat detection, compliance dashboards | — |
| SIEM Use Cases Supported(count) | 400+ built-in detections | — |
| Mobile App Platform Support | iOS & Android (full-featured) | — |
| Fortune 500 Adoption Rate(percent) | 70%+ | — |
| Number of Integrations(count) | 600+ | 900+(winner) |
| Number of Pre-built Integrations(count) | 700+(winner) | 600+ |
| Third-party Integrations(count) | 2,000+ apps | — |
| Machine Learning Capabilities(availability) | Incident pattern detection only | Full ML for anomaly detection, forecasting, root cause analysis |
| Machine Learning Sophistication(capability level) | Basic correlation & anomaly detection | Advanced: forecasting, clustering, outlier detection |
| Machine Learning Use Cases Included(count) | 15+ (threat detection, predictive analytics, correlation, clustering) | — |
| FedRAMP Authorization(boolean) | Not authorized | FedRAMP Authorized |
| Native Integrations(count) | 5,000+ | — |
| Alert Deduplication Method | ML-driven with event correlation | — |
| Average Onboarding Time(days) | 5-7 days | — |
| Typical Deployment Timeline(weeks) | 7 weeks | — |
| Initial Deployment Time(minutes) | 2,880 (4-8 weeks average) | — |
| Founded Year(year) | 2009 | — |
| Query Language Learning Curve(complexity rating) | Low (UI-driven workflows) | High (SPL requires training) |
| Machine Learning Models(count) | 50+ algorithms | — |
| Mean Time to Detection (MTTD)(minutes) | 15-60 minutes (depends on alert configuration) | — |
| Malware Detection Rate(%) | Varies by threat rules configured | — |
| Automated Response Actions(native actions) | Via SOAR integration (external) | — |
| Maximum Cluster Nodes(nodes) | Unlimited (license-dependent) | — |
| Maximum Data Ingestion Per Day (Enterprise)(GB) | Unlimited (licensing dependent) | — |
| Community Support Response Time(hours) | 1 (24/7 enterprise SLA) | — |
| Default Data Retention Period(months) | 120 months (10 years) | — |
| Gartner Magic Quadrant Position (2024)(text) | Leader | — |
| Learning Curve (Time to Productivity)(weeks) | 4-6 weeks | — |
| APM Trace Sampling Depth(percent) | Sampling-dependent (configurable) | — |
| Enterprise Customers(millions) | 10,000+ (2024) | — |
| Minimum RAM Requirement (Self-Hosted)(GB) | 8+ | — |
| GitHub Stars (Community Adoption)(stars) | 2,500+ (proprietary, less open) | — |
| Default Metrics Retention(days) | 30 (upgradeable to unlimited) | — |
| Default Log Retention (free tier)(days) | Not offered | — |
PPagerDuty
SplunkStarting Monthly Cost per User(USD)
$49
—
Free Trial Period(days)
14 days
—
Base Monthly Cost Per User(USD)
$49
—
Free Tier User Limit(users)
3 users
—
Base Monthly Cost (10 users)(USD)
$490/month
—
Show 21 more attributes
Cost at 100 Users(USD/month)
$4,900/month
—
Base Annual Cost(USD)
$1,449
$2,400
Additional Data Ingestion Cost(USD per 10GB/day)
N/A - not data-focused
$250-350
Base Monthly Cost (5 Users, Annual Commitment)(USD/month)
$1,495
—
Atlassian Bundle Discount(percent)
0%
—
Base Monthly Pricing(USD)
$49/user
—
Starting Annual Cost(USD)
$1,500
$4,500
Cost per 100 Users (Annual)(USD)
$15,000-$25,000
$36,000-$180,000
Base Monthly Cost (100GB/day)(USD)
$3,500-$5,500
—
Annual TCO (1TB/day ingestion)(USD)
$450,000-$750,000
—
Starting Annual Cost (single user/endpoint)(USD)
$3,000-6,000
—
Base Annual Cost (Small Deployment)(USD)
$3,000 - $5,000
—
Per-Gigabyte Ingestion Cost(USD per GB per day)
$0.80 - $1.50
—
Average Cost per GB Ingested(USD)
$1.50
—
Monthly Cost (100GB/day ingestion)(USD)
$10,000-25,000
—
Base Monthly Cost (Single User Cloud)(USD)
$4,500+ (minimum commitment)
—
Annual Cost (1GB/day Log Ingestion)(USD)
$54,000-$108,000
—
Base Monthly Pricing (1GB/day ingestion)(USD)
$1,500-$2,000
—
Base License Cost (Annual)(USD)
$5,000 minimum
—
Typical Enterprise Implementation Cost(USD)
$50,000-$200,000
—
Minimum Monthly Commitment(USD)
$3,600 ($120/day minimum)
—
Available Integrations(integrations)
600+
—
Available Integrations(count)
500+
—
Pre-built Integrations/Apps(count)
800+ apps in Splunkbase
—
Mobile App Rating(quality level)
4.8/5
—
Jira Integration Depth
API-based integration
—
Data Source Integrations(count)
200+ integrations
—
Jira Sync Capability
One-way basic plugin sync
—
Multi-tenant Deployment Options
Cloud, hybrid, self-hosted (enterprise)
—
Open-Source Self-Hosted Availability(null)
Enterprise tier only
—
Average Implementation Timeline(weeks)
3
8
Agent Size/System Footprint(MB)
Heavy (varies, 500MB+)
—
Setup Time to Production(minutes)
4-8 (managed cloud)
—
Show 1 more attribute
Implementation Timeline(weeks)
14-42 days
—
Uptime SLA Guarantee(percentage)
99.99%
—
Uptime SLA Guarantee(percent)
99.95%
—
Estimated Global Market Share(percentage)
28%
—
Customers (Approximate)(count)
10,000+
—
Gartner SIEM Market Share(percent)
28% (2024)
—
Enterprise Customer Count (2025)(organizations)
12,000
—
Mean Time to Response (MTTR) Improvement(percent)
58% faster
—
Alert Fatigue Reduction(percent)
60% via deduplication
—
Alert Grouping Reduction(%)
75% alert noise reduction
—
MTTR Improvement vs Manual(%)
87% faster
—
Average Incident Resolution Time Improvement(percent)
35% faster (reported by customers)
—
Show 16 more attributes
Time to Incident Creation from Alert(seconds)
<60 seconds
Not applicable (generates alerts)
Mobile Push Notification Latency(seconds)
<2 seconds
—
Data Ingestion Capacity (Standard Plan)(GB/day)
Alerts: unlimited routing
500GB
Maximum Alerts Per Minute Capacity(alerts/min)
10,000+
Limited by ingestion
Deployment Time(seconds)
21-30 days
—
Default Data Retention(days)
30 days included
—
Query Performance (5TB dataset)(seconds)
8-12 seconds
—
Query Response Time (1B records)(milliseconds)
100-300ms
—
APM Real-Time Metric Resolution(seconds)
10-30 seconds
—
Time-to-First-Alert(minutes)
15-30 minutes
—
Log Query Response Time(milliseconds)
<100
—
Event Ingestion Rate (Single Indexer)(events/sec)
10,000+
—
Query Response Time (1GB dataset)(milliseconds)
2,000-5,000ms
—
Average Search Query Time (1GB dataset)(seconds)
1-5 seconds
—
Typical Deployment Time(minutes)
8-16 weeks
—
Log Ingestion at $10k/Month Spend(GB per day)
~200
—
Customer Retention Rate(percent)
96%
—
Native Monitoring Capabilities(integrations)
400+ via integrations
—
Log Retention Standard Plan(days)
Not included
—
Native APM Included
No (integration only)
—
On-Call Scheduling Features(null)
Native, advanced rotation policies
—
Native Integrations Available(integrations)
600+
—
Show 16 more attributes
Mobile App Incident Management(availability)
Full (scheduling, ack, resolve on mobile)
Limited (dashboards only)
Standard Data Retention(days)
N/A - incident focused
30-365 days
Communication Channels Supported(count)
6 channels
—
On-Call Scheduling Complexity
Advanced (rotations, overrides, patterns)
—
Post-Incident Review Capability
Basic manual reviews
—
Built-in Collaboration Space
Chat integration required
—
Out-of-Box Integrations(count)
700+ integrations
—
Default Data Retention (included in pricing)(months)
12 months
—
Native Data Source Integrations(count)
400+
—
Built-in Machine Learning Algorithms(count)
50+
—
APM Distributed Tracing(languages supported)
Limited (add-on required)
—
Pre-built Integrations(count)
300+
—
Data Sources Supported(integrations)
150+ (broader enterprise data ecosystem)
—
Full-Text Log Indexing
Yes (native)
—
Built-in Machine Learning Models(count)
20+ (anomaly detection, forecasting, UEBA)
—
Native APM Capability
Requires add-on license ($X additional)
—
Typical Setup Time(hours)
8-16 hours
—
Founding Year
2010
—
Enterprise SSO (SAML/OAuth)
Yes
—
Built-in Compliance Certifications(count)
6 (HIPAA, SOC2, PCI-DSS, FedRAMP, GDPR, ISO27001)
—
SIEM Compliance Modules (pre-built)(count)
12 (HIPAA, PCI, SOC2, NIST)
—
Enterprise Security Features(count)
Enterprise Security module, threat detection, compliance dashboards
—
SIEM Use Cases Supported(count)
400+ built-in detections
—
Mobile App Platform Support
iOS & Android (full-featured)
—
Fortune 500 Adoption Rate(percent)
70%+
—
Number of Integrations(count)
600+
900+
Number of Pre-built Integrations(count)
700+
600+
Third-party Integrations(count)
2,000+ apps
—
Machine Learning Capabilities(availability)
Incident pattern detection only
Full ML for anomaly detection, forecasting, root cause analysis
Machine Learning Sophistication(capability level)
Basic correlation & anomaly detection
Advanced: forecasting, clustering, outlier detection
Machine Learning Use Cases Included(count)
15+ (threat detection, predictive analytics, correlation, clustering)
—
FedRAMP Authorization(boolean)
Not authorized
FedRAMP Authorized
Native Integrations(count)
5,000+
—
Alert Deduplication Method
ML-driven with event correlation
—
Average Onboarding Time(days)
5-7 days
—
Typical Deployment Timeline(weeks)
7 weeks
—
Initial Deployment Time(minutes)
2,880 (4-8 weeks average)
—
Founded Year(year)
2009
—
Query Language Learning Curve(complexity rating)
Low (UI-driven workflows)
High (SPL requires training)
Machine Learning Models(count)
50+ algorithms
—
Mean Time to Detection (MTTD)(minutes)
15-60 minutes (depends on alert configuration)
—
Malware Detection Rate(%)
Varies by threat rules configured
—
Automated Response Actions(native actions)
Via SOAR integration (external)
—
Maximum Cluster Nodes(nodes)
Unlimited (license-dependent)
—
Maximum Data Ingestion Per Day (Enterprise)(GB)
Unlimited (licensing dependent)
—
Community Support Response Time(hours)
1 (24/7 enterprise SLA)
—
Default Data Retention Period(months)
120 months (10 years)
—
Gartner Magic Quadrant Position (2024)(text)
Leader
—
Learning Curve (Time to Productivity)(weeks)
4-6 weeks
—
APM Trace Sampling Depth(percent)
Sampling-dependent (configurable)
—
Enterprise Customers(millions)
10,000+ (2024)
—
Minimum RAM Requirement (Self-Hosted)(GB)
8+
—
GitHub Stars (Community Adoption)(stars)
2,500+ (proprietary, less open)
—
Default Metrics Retention(days)
30 (upgradeable to unlimited)
—
Default Log Retention (free tier)(days)
Not offered
—
Pros & Cons
10 pros·6 cons across both
P
P
PagerDuty
+5-3
Pros
- Intelligent alert routing reduces alert noise by 50-70% through deduplication and correlation
- 700+ pre-built integrations with monitoring tools (Datadog, New Relic, Prometheus, AWS CloudWatch)
- Rapid deployment: 2-4 weeks average implementation vs 4-12 weeks for competitors
- Comprehensive on-call scheduling with automatic escalation, schedule overrides, and calendar sync
- REST API and webhook support enable extensive customization and workflow automation
Cons
- Limited data analysis capabilities; not designed for log searching or complex queries
- Requires integration with external monitoring tools; doesn't ingest raw machine data
- Per-user pricing scales quickly for large teams (can exceed $100k annually for 200+ users)
Splunk
+5-3
Pros
- Ingests up to 5TB+ of data daily with powerful search and analysis across petabytes of indexed data
- Advanced Machine Learning Toolkit for anomaly detection, forecasting, and predictive analytics
- Splunk Enterprise Security (ES) module provides SIEM capabilities with threat detection and compliance reporting
- 600+ pre-built apps and add-ons for industry-specific use cases (healthcare, finance, retail)
- Real-time alerting and on-call management via Splunk On-Call (formerly VictorOps, acquired 2020)
Cons
- High implementation complexity: 4-12 weeks typical onboarding; requires skilled data engineers
- Per-gigabyte-per-day pricing creates unpredictable costs; 1TB/day can cost $50k-$150k annually
- Steep learning curve; SPL (Splunk Processing Language) requires training and expertise
Frequently Asked Questions
5 questions
Yes. Splunk can send alerts to PagerDuty through native integration or webhooks. PagerDuty then handles routing and on-call escalation, while Splunk provides the underlying analytics and root cause investigation. This is a common enterprise pattern where Splunk detects issues and PagerDuty manages the response.
Resources & Learn More
Curated sources to dive deeper
Where to Buy
As an affiliate, we may earn a commission from qualifying purchases at no extra cost to you. Learn more about our affiliate disclosure
Wikipedia
- W
PagerDuty on Wikipedia (opens in new tab)
Incident response and on-call management platform for alert orchestration and team coordination.
- W
Splunk on Wikipedia (opens in new tab)
Data analytics platform for ingesting, indexing, and analyzing machine-generated data from applications, infrastructure, and security systems.
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