software
Domo vs Looker 2026: BI Comparison
Domo is a cloud-native BI platform optimized for business users with drag-and-drop simplicity and strong mobile capabilities, while Looker is a developer-centric embedded analytics tool owned by Google with superior SQL-based modeling and enterprise scalability. Domo excels at self-service analytics; Looker dominates in complex data infrastructure and white-label deployment.
D
Domo
Cloud-native BI platform focused on self-service analytics and business user empowerment.
Mid-market companies with non-technical power users, rapid deployment needs, and strong mobile analytics requirements
Score63%
VS
Looker
Enterprise analytics platform owned by Google specializing in embedded analytics and sophisticated data modeling via LookML.
Large enterprises, SaaS companies needing embedded analytics, organizations with dedicated analytics engineering teams, and Google Cloud-first organizations
Score63%
Quick Answer
AI SummaryDomo is a cloud-native BI platform optimized for business users with drag-and-drop simplicity and strong mobile capabilities, while Looker is a developer-centric embedded analytics tool owned by Google with superior SQL-based modeling and enterprise scalability. Domo excels at self-service analytics; Looker dominates in complex data infrastructure and white-label deployment.
Our Verdict
AI-assistedChoose Domo if your organization prioritizes ease-of-use, rapid time-to-value, and empowering non-technical business users with self-service analytics capabilities. Choose Looker if you need robust data governance, embedded analytics for customer-facing applications, complex multi-source data modeling, or are already invested in the Google Cloud ecosystem and can allocate technical resources for implementation.
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D
Domo
8.2/10
Looker
6.8/10
D
Choose Domo if
Best pickMid-market companies with non-technical power users, rapid deployment needs, and strong mobile analytics requirements
Choose Looker if
Large enterprises, SaaS companies needing embedded analytics, organizations with dedicated analytics engineering teams, and Google Cloud-first organizations
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Key Differences at a Glance
- Primary Use Case:Self-service business analytics & dashboards vs Embedded analytics & data modeling
- Data Modeling Approach:✓ Looker wins(LookML (proprietary language) with full SQL flexibility vs Visual/UI-based with limited SQL control)
- Implementation Complexity:✓ Domo wins(2-4 weeks (business-user friendly) vs 4-12 weeks (requires technical expertise))
Key Facts & Figures
112 numeric metrics compared
| Metric | Domo | Looker | Ratio |
|---|---|---|---|
| Enterprise Security Certifications(count) | SOC 2 Type II, HIPAA, FedRAMP | — | — |
| Monthly Subscription Cost (Enterprise)(USD) | $3,500 (average) | — | — |
| Typical Org Size (Target)(employees) | 500+ (enterprise) | — | — |
| Starting Annual Price(USD) | $5,000 entry-level | — | — |
| Average Dashboard Load Time(seconds) | 2-3 seconds | — | — |
| Typical Implementation Time(days) | 2-4 weeks | 7-14 days | |
| Free Trial Period(days) | 30 days | 14 days | |
| User Adoption Rate (Typical)(percent) | 75% within 60 days | — | — |
| Support Tier - Response Time (Premium)(hours) | 1 hour | — | — |
| Minimum Annual Cost (Enterprise)(USD) | $100,000 | $70,000 | |
| Average Implementation Duration(weeks) | 2.5 weeks | 8 weeks | |
| Customization Flexibility (1-10 scale)(score) | 6/10 (Visual builders) | 9/10 (LookML code control) | |
| Non-Technical User Friendliness (1-10 scale)(score) | 8.5/10 (drag-and-drop design) | 5/10 (requires technical knowledge) | |
| Starting Annual Cost(USD) | $5,000 | — | — |
| Cost for 100-User Organization (Annual)(USD) | $25,000 - $50,000 | — | — |
| Global Market Share (2025)(percent) | 2.4% | — | — |
| Time to Create First Dashboard(hours (for beginner)) | 20-30 | — | — |
| Base Annual Cost (Single User)(USD) | $60,000+ | — | — |
| Data Connectors Available(count) | 700+ | 800+ (via Fivetran) | |
| Query Latency (100M rows)(milliseconds) | <500ms | — | — |
| Average Implementation Timeline(weeks) | 2-4 weeks | 10 weeks | |
| Minimum Team Training Required(weeks) | 4-6 weeks | — | — |
| Starting Price (per user/month)(USD) | $500+ (org-wide minimum) | — | — |
| Pre-built Data Connectors(count) | 500+ | — | — |
| Typical Implementation Timeline(weeks) | 4-8 months | 8-16 weeks | |
| Visualization Types Available(count) | 90+ | 50+ visualizations | |
| Starting Monthly Cost Per User(USD) | $35 | — | — |
| Native Data Connectors Available(count) | 70+ | — | — |
| Mobile App Usability Rating(score out of 10) | 8.2/10 | — | — |
| Time to First Dashboard(weeks) | 0.75 hours | 6-12 weeks | |
| Global BI Platform Market Share(percent) | 11.2% | — | — |
| G2 Customer Satisfaction Score(out of 5 stars) | 4.5/5 | — | — |
| Average Implementation Time(days) | 4-8 weeks | 2-4 weeks | |
| Native Data Connectors(connectors) | 300+ | 1,000+ | |
| Query Response Time (10B rows)(seconds) | 5-15 | — | — |
| Typical Enterprise Implementation(weeks) | 8-16 | — | — |
| Annual License Cost (500 users)(USD) | $400,000-$800,000 | — | — |
| Non-Technical User Self-Service Rate(percent) | 90% | — | — |
| Mobile App Store Rating(stars) | 4.3/5 (2,400 reviews) | — | — |
| Maximum Data Model Size(GB) | 500 GB (with optimization) | — | — |
| Starting Price (Monthly per User)(USD) | $500 | — | — |
| Enterprise Edition Annual Cost per User(USD) | $2,400 | — | — |
| Global Active Users(millions) | 0.15M | — | — |
| Maximum Dataset Size (Optimal Performance)(rows) | 50M rows | — | — |
| Analyst Proficiency Learning Period(weeks) | 2-3 weeks | — | — |
| Number of Native Data Connectors(count) | 600+ | 250+ | |
| Starting Enterprise Contract Value(USD per year) | $50,000 | $180,000 | |
| Maximum Recommended Dataset Size(rows) | 500 million | 10 billion+ | |
| Percentage of Use Cases Needing Code(percent) | 15% | 40% | |
| Average Monthly Cost Per User(USD) | $800-$3,000 | — | — |
| Maximum Concurrent Users Supported(users) | Unlimited (cloud-native) | 10,000+ | — |
| AI/ML Automation Capabilities(score) | Basic (predictive only) | — | — |
| Maximum Dataset Size Supported(GB) | 500GB+ (with optimization) | — | — |
| User Interface Complexity Rating(score) | Complex (steep curve) | — | — |
| Starting Price (Annual)(USD) | $24,000 | $24,000 | |
| Setup Time(minutes) | 4-8 weeks | 4-8 weeks | |
| Data Connectors(count) | 60+ | 60+ | |
| User Permissions Roles(levels) | Unlimited custom RBAC | Unlimited custom RBAC | |
| Query Speed (Caching)(ms) | 500-2000 | 500-2000 | |
| Maximum Dashboard Users(per plan) | Unlimited (enterprise) | Unlimited (enterprise) | |
| Market Share (2025)(%) | 8-10% | 8-10% | |
| Typical Implementation Timeline(months) | 4-6 months | 4-6 months | |
| Learning Curve Difficulty(scale 1-10) | 7/10 (Steep) | 7/10 (Steep) | |
| Data Connectors Available(count) | 200+ | 200+ | |
| Starting Cost (Annual, Single User)(USD) | $24,000-60,000 | $24,000-60,000 | |
| Starting Price Per User (Annual)(USD) | $3,000 | $3,000 | |
| Implementation Timeline(weeks) | 18-26 weeks | 18-26 weeks | |
| Business User Learning Time(days) | 14-21 days | 14-21 days | |
| Native Database Connectors(count) | 200+ | 200+ | |
| Query Performance (Sub-second)(milliseconds) | 500-2000ms | 500-2000ms | |
| API Rate Limit(requests per second) | 1,000 RPM | 1,000 RPM | |
| Base Monthly Cost Per User(USD) | $24/month | $24/month | |
| Annual Cost (100 Users)(USD) | $28,800 | $28,800 | |
| Global Market Share(%) | 12.5% | 12.5% | |
| Starting Annual Cost (Small Org)(USD) | $50,000+ | $50,000+ | |
| Maximum Dataset Size (Optimized)(GB) | 100+ GB | 100+ GB | |
| Query Response Time (100GB dataset)(seconds) | 2-5 seconds | 2-5 seconds | |
| Self-Service Analytics Maturity(1-10 scale) | 5/10 (requires LookML expertise) | 5/10 (requires LookML expertise) | |
| Average Training Hours Required (Per Analyst)(hours) | 40-60 hours | 40-60 hours | |
| Total Cost of Ownership (First Year, 10 Users)(USD) | $6,000-$12,000 (minimum enterprise license) | $6,000-$12,000 (minimum enterprise license) | |
| Data Connector Integrations(count) | 600+ integrations | 600+ integrations | |
| Starting Annual Cost (Single User)(USD) | $2,000 | $2,000 | |
| Typical Enterprise Implementation Timeline(weeks) | 12 weeks average | 12 weeks average | |
| Learning Curve (Hours to First Dashboard)(hours) | 40-60 hours (with developer background) | 40-60 hours (with developer background) | |
| Global Active Users (2026)(millions) | 1.2+ million | 1.2+ million | |
| Maximum Concurrent Users(users) | 5,000+ users | 5,000+ users | |
| Learning Curve (Days to First Dashboard)(days) | 5-10 days | 5-10 days | |
| Starting Price (Annual, 10 Users)(USD) | $45,000 | $45,000 | |
| Time to Deploy First Dashboard(minutes) | 14-21 days | 14-21 days | |
| Data Connectors Supported(count) | 70+ connectors | 70+ connectors | |
| Semantic Layer Maturity(scale 1-10) | 9/10 (centralized LookML) | 9/10 (centralized LookML) | |
| Enterprise Market Share(%) | 12% | 12% | |
| Learning Curve for Non-Technical Users(hours to first dashboard) | 40-80 hours | 40-80 hours | |
| Data Source Connectors(count) | 300+ | 300+ | |
| Visualization Types(count) | 80+ chart types | 80+ chart types | |
| Base Starter Price (Annual)(USD) | $3,000 per core minimum | $3,000 per core minimum | |
| Implementation Time (typical)(weeks) | 8-12 weeks (requires modeling) | 8-12 weeks (requires modeling) | |
| Mobile App Completeness(feature parity %) | 60% of desktop features | 60% of desktop features | |
| BigQuery Query Speed(milliseconds) | Average 800ms for 100M rows | Average 800ms for 100M rows | |
| Base Annual Cost Per User(USD) | $2,000 - $5,000 | $2,000 - $5,000 | |
| Enterprise BI Market Share(%) | 8-12% | 8-12% | |
| Data Sources Supported(integrations) | 80+ connectors | 80+ connectors | |
| Available Chart Types(count) | 60+ visualization types | 60+ visualization types | |
| Average Query Response Time(seconds) | 3.5 seconds | 3.5 seconds | |
| Starting Enterprise License(USD annually) | $70,000 | $70,000 | |
| Typical User Training Required(hours) | 40-80 hours | 40-80 hours | |
| Starting Monthly Cost (SaaS)(USD) | $2,000 | $2,000 | |
| Number of Native Connectors(connectors) | 90+ | 90+ | |
| Max Concurrent Users (Recommended)(users) | 100+ | 100+ | |
| Available Data Connectors(integrations) | 750+ | 750+ | |
| Starting User Cost (Annual)(USD per user) | $600-$3,200 | $600-$3,200 | |
| Typical Mid-Market Annual Contract Value(USD) | $200,000-$500,000 | $200,000-$500,000 |
Sourced from publicly available data ·
Key Differences
7 attributes compared head-to-head
D
3DomoEvenly matched1 tie
Domo
Attribute
Looker
- Self-service business analytics & dashboardsPrimary Use CaseEmbedded analytics & data modeling
- Visual/UI-based with limited SQL controlData Modeling ApproachLookML (proprietary language) with full SQL flexibility(winner)
- 2-4 weeks (business-user friendly)(winner)Implementation Complexity4-12 weeks (requires technical expertise)
- Native mobile app with offline capabilities(winner)Mobile ExperienceWeb-responsive, limited native mobile features
- $150,000-$300,000(winner)Typical Annual Cost (Mid-Market)$200,000-$500,000
- Limited, not primary strengthWhite-Label/Embedded CapabilityExcellent, core strength with full branding control(winner)
- Mid-market to enterprise (500+ employees)Enterprise Client BaseLarge enterprises (5,000+ employees)(winner)
- Primary Use Case
Domo
Self-service business analytics & dashboards
Looker
Embedded analytics & data modeling
- Data Modeling Approach
Domo
Visual/UI-based with limited SQL control
Looker
LookML (proprietary language) with full SQL flexibility(winner)
- Implementation Complexity
Domo
2-4 weeks (business-user friendly)(winner)
Looker
4-12 weeks (requires technical expertise)
- Mobile Experience
Domo
Native mobile app with offline capabilities(winner)
Looker
Web-responsive, limited native mobile features
- Typical Annual Cost (Mid-Market)
Domo
$150,000-$300,000(winner)
Looker
$200,000-$500,000
- White-Label/Embedded Capability
Domo
Limited, not primary strength
Looker
Excellent, core strength with full branding control(winner)
- Enterprise Client Base
Domo
Mid-market to enterprise (500+ employees)
Looker
Large enterprises (5,000+ employees)(winner)
Full Comparison
| Attribute | Domo | Looker |
|---|---|---|
| Enterprise Security Certifications(count) | SOC 2 Type II, HIPAA, FedRAMP | — |
| Row-Level Security Granularity(text) | Static (role-based) | Field, row, and dashboard-level |
| User Permissions Roles(levels) | Unlimited custom RBAC | — |
| Data Governance Features(comprehensive level) | Enterprise-grade with LookML controls | — |
| Enterprise Compliance Certifications(count) | SOC 2 Type II, ISO 27001, HIPAA, FedRAMP (GCP) | — |
Show 1 more attributeRow-Level Security (RLS) Complexity(capability level) Advanced contextual RLS with LookML — | ||
| GitHub Community Stars(stars) | Limited public info | — |
| GitHub Stars (Community Adoption)(stars) | Not open-source | — |
| Monthly Subscription Cost (Enterprise)(USD) | $3,500 (average) | — |
| Starting Annual Price(USD) | $5,000 entry-level | — |
| Minimum Annual Cost (Enterprise)(USD) | $100,000 | $70,000(winner) |
| Starting Annual Cost(USD) | $5,000 | — |
| Cost for 100-User Organization (Annual)(USD) | $25,000 - $50,000 | — |
Show 22 more attributesBase Annual Cost (Single User)(USD) $60,000+ — Starting Price (per user/month)(USD) $500+ (org-wide minimum) — Starting Monthly Cost Per User(USD) $35 — Annual License Cost (500 users)(USD) $400,000-$800,000 — Starting Enterprise Contract Value(USD per year) $50,000 $180,000 Average Monthly Cost Per User(USD) $800-$3,000 — Starting Price (Annual)(USD) $24,000 — Starting Cost (Annual, Single User)(USD) $24,000-60,000 — Starting Price Per User (Annual)(USD) $3,000 — Base Monthly Cost Per User(USD) $24/month — Annual Cost (100 Users)(USD) $28,800 — Starting Annual Cost (Small Org)(USD) $50,000+ — Total Cost of Ownership (First Year, 10 Users)(USD) $6,000-$12,000 (minimum enterprise license) — Starting Annual Cost (Single User)(USD) $2,000 — Starting Price (Annual, 10 Users)(USD) $45,000 — Base Starter Price (Annual)(USD) $3,000 per core minimum — Base Annual Cost Per User(USD) $2,000 - $5,000 — Starting Enterprise License(USD annually) $70,000 — Starting Monthly Cost (SaaS)(USD) $2,000 — Self-Hosting Cost(USD) Not available — Starting User Cost (Annual)(USD per user) $600-$3,200 — Typical Mid-Market Annual Contract Value(USD) $200,000-$500,000 — | ||
| AI/Predictive Analytics | Built-in with automated insight discovery | — |
| Embedded Analytics Capability(null) | Basic (limited white-label) | Purpose-built, highly white-labelable |
| Mobile App Capability | Native iOS/Android with full features | Web-responsive, limited interactivity |
| Customization Flexibility (1-10 scale)(score) | 6/10 (Visual builders) | 9/10 (LookML code control)(winner) |
| AI-Powered Insights | Domo AI with natural language queries | Limited predictive models |
Show 14 more attributesWorkflow Automation Capabilities Advanced (alerts, scheduling, actions) — Native Workflow Automation(null) Yes - alerts, routing, task execution — Visualization Types Available(count) 90+ 50+ visualizations Native Mobile App Support(null) Yes (with offline mode) — White-Label Embedding Capability(capability level) Limited / add-on cost Enterprise SDK included Mobile App Functionality(percentage) 95% (with offline mode) — Mobile App Native iOS/Android + responsive web — API Capabilities Advanced GraphQL and REST APIs — Embedded Analytics Support(capability score) Excellent - Native support — Enterprise Embedded Analytics Support(tier level) Native in all plans — Visualization Types(count) 80+ chart types — Data Sources Supported(integrations) 80+ connectors — Available Chart Types(count) 60+ visualization types — Custom Modeling Language LookML (proprietary) — | ||
| Deployment Flexibility | Cloud-only (SaaS) | — |
| Deployment Options | Cloud (SaaS only) | — |
| Typical Org Size (Target)(employees) | 500+ (enterprise) | — |
| Average Dashboard Load Time(seconds) | 2-3 seconds | — |
| Query Latency (100M rows)(milliseconds) | <500ms | — |
| Data Refresh Rate(times per day) | Real-time (unlimited) | — |
| Query Response Time (10B rows)(seconds) | 5-15 | — |
| Maximum Dataset Size (Optimal Performance)(rows) | 50M rows | — |
Show 9 more attributesMaximum Recommended Dataset Size(rows) 500 million 10 billion+ Maximum Dataset Size Supported(GB) 500GB+ (with optimization) — Query Speed (Caching)(ms) 500-2000 — Query Performance (Sub-second)(milliseconds) 500-2000ms — Maximum Dataset Size (Optimized)(GB) 100+ GB — Query Response Time (100GB dataset)(seconds) 2-5 seconds — BigQuery Native Optimization(null) Full automatic caching and pushdown — BigQuery Query Speed(milliseconds) Average 800ms for 100M rows — Average Query Response Time(seconds) 3.5 seconds — | ||
| Typical Implementation Time(days) | 2-4 weeks(winner) | 7-14 days |
| Average Implementation Duration(weeks) | 2.5 weeks(winner) | 8 weeks |
| Average Implementation Timeline(weeks) | 2-4 weeks(winner) | 10 weeks |
| Typical Implementation Timeline(weeks) | 4-8 months(winner) | 8-16 weeks |
| Typical Enterprise Implementation(weeks) | 8-16 | — |
Show 6 more attributesTypical Implementation Timeline(months) 4-6 months — Implementation Timeline(weeks) 18-26 weeks — Typical Enterprise Implementation Timeline(weeks) 12 weeks average — Cloud Architecture Model(null) Cloud-native SaaS (single-tenant) — Implementation Time (typical)(weeks) 8-12 weeks (requires modeling) — Supported Cloud Platforms(count) 1 (Google Cloud native) — | ||
| Maximum Concurrent Users (Standard Plan)(users) | Unlimited (license-based) | — |
| Maximum Data Model Size(GB) | 500 GB (with optimization) | — |
| Maximum Concurrent Users Supported(users) | Unlimited (cloud-native) | 10,000+ |
| Maximum Dashboard Users(per plan) | Unlimited (enterprise) | — |
| Maximum Concurrent Users(users) | 5,000+ users | — |
Show 1 more attributeMax Concurrent Users (Recommended)(users) 100+ — | ||
| Free Trial Period(days) | 30 days(winner) | 14 days |
| Average Implementation Time(days) | 4-8 weeks | 2-4 weeks(winner) |
| User Adoption Rate (Typical)(percent) | 75% within 60 days | — |
| Mobile App Usability Rating(score out of 10) | 8.2/10 | — |
| Setup Time(minutes) | 4-8 weeks | — |
| Mobile App Native Support(capability level) | Web-responsive design, limited mobile | — |
| Support Tier - Response Time (Premium)(hours) | 1 hour | — |
| Database Query Language Support | SQL via connectors, limited direct database access | Native SQL, complex joins, window functions |
| Data Connectors Available(count) | 700+ | 800+ (via Fivetran)(winner) |
| Google Workspace Integration | Partial - via connectors | — |
| Native Excel Integration | Limited, requires API | — |
| Pre-built Data Connectors(count) | 500+ | — |
Show 10 more attributesNative Data Connectors Available(count) 70+ — Native Data Connectors(connectors) 300+ 1,000+ Number of Native Data Connectors(count) 600+ 250+ Data Connectors(count) 60+ — Data Connectors Available(count) 200+ — Native Database Connectors(count) 200+ — Data Connector Integrations(count) 600+ integrations — Data Connectors Supported(count) 70+ connectors — Data Source Connectors(count) 300+ — Number of Native Connectors(connectors) 90+ — | ||
| Non-Technical User Friendliness (1-10 scale)(score) | 8.5/10 (drag-and-drop design)(winner) | 5/10 (requires technical knowledge) |
| Non-Technical User Self-Service Rate(percent) | 90% | — |
| Analyst Proficiency Learning Period(weeks) | 2-3 weeks | — |
| User Interface Complexity Rating(score) | Complex (steep curve) | — |
| Learning Curve Difficulty(scale 1-10) | 7/10 (Steep) | — |
Show 4 more attributesBusiness User Learning Time(days) 14-21 days — Self-Service Analytics Maturity(1-10 scale) 5/10 (requires LookML expertise) — Learning Curve (Hours to First Dashboard)(hours) 40-60 hours (with developer background) — Learning Curve for Non-Technical Users(hours to first dashboard) 40-80 hours — | ||
| Global Market Share (2025)(percent) | 2.4% | — |
| Global BI Platform Market Share(percent) | 11.2% | — |
| Market Share (2025)(%) | 8-10% | — |
| Global Market Share(%) | 12.5% | — |
| Enterprise Market Share(%) | 12% | — |
Show 1 more attributeEnterprise BI Market Share(%) 8-12% — | ||
| Time to Create First Dashboard(hours (for beginner)) | 20-30 | — |
| Requires SQL/Code Knowledge(boolean) | No, drag-and-drop | — |
| Percentage of Use Cases Needing Code(percent) | 15%(winner) | 40% |
| Learning Curve (Days to First Dashboard)(days) | 5-10 days | — |
| Learning Curve Complexity(1–10 scale) | Advanced (requires SQL/LookML) | — |
| Built-in ETL/Data Integration | Advanced (native) | — |
| Visualization Customization Level | Good (operational focus) | — |
| AI/ML Automation Capabilities(score) | Basic (predictive only) | — |
| Machine Learning / AI Features | Looker Studio, Einstein AI, predictive analytics | — |
| Mobile App Editing Capability(text) | Full feature parity with desktop | — |
| Minimum Team Training Required(weeks) | 4-6 weeks | — |
| Mobile Dashboard Editing | Full editing capabilities | — |
| Built-in Data Governance Tools | Native data certification & lineage | — |
| Row-Level Security (RLS) Support | Native RLS with attribute-based access | — |
| Time to First Dashboard(weeks) | 0.75 hours(winner) | 6-12 weeks |
| G2 Customer Satisfaction Score(out of 5 stars) | 4.5/5 | — |
| Real-time Collaboration Features | Built-in | — |
| Mobile App Store Rating(stars) | 4.3/5 (2,400 reviews) | — |
| Built-in ETL Transformation(yes/no) | Yes (Domo Connector Framework) | — |
| Starting Price (Monthly per User)(USD) | $500 | — |
| Enterprise Edition Annual Cost per User(USD) | $2,400 | — |
| Global Active Users(millions) | 0.15M | — |
| Mobile App Dashboard Interactivity(capability level) | Full interactivity + alerts | Read-only |
| Mobile App Completeness(feature parity %) | 60% of desktop features | — |
| Mobile App Quality | 4/5 stars | — |
| API Rate Limit(requests per second) | 1,000 RPM | — |
| Data Model Customization Depth(complexity level) | Advanced (custom dimensions, measures, derived tables) | — |
| Average Training Hours Required (Per Analyst)(hours) | 40-60 hours | — |
| Semantic Layer Capability | Advanced (LookML semantic layer) | — |
| Global Active Users (2026)(millions) | 1.2+ million | — |
| Typical User Training Required(hours) | 40-80 hours | — |
| Semantic Layer (Metric Consistency)(null) | Native LookML ensures single source of truth | — |
| Semantic Layer Strength(governance level) | Built-in (LookML) - single source of truth | — |
| Centralized Metric Management(text) | LookML semantic layer with version control | — |
| Time to Deploy First Dashboard(minutes) | 14-21 days | — |
| Semantic Layer Maturity(scale 1-10) | 9/10 (centralized LookML) | — |
| Mobile App Support | Limited; primarily desktop-focused | — |
| Natural Language Query Capability(text) | Basic Explore interface (code-based) | — |
| Open Source Availability | Closed source (Google proprietary) | — |
| Available Data Connectors(integrations) | 750+ | — |
| Embedded Analytics Suitability(rating) | Excellent (core platform strength) | — |
| SQL Modeling Flexibility(capability level) | Unrestricted (LookML + native SQL) | — |
DDomo
LookerEnterprise Security Certifications(count)
SOC 2 Type II, HIPAA, FedRAMP
—
Row-Level Security Granularity(text)
Static (role-based)
Field, row, and dashboard-level
User Permissions Roles(levels)
Unlimited custom RBAC
—
Data Governance Features(comprehensive level)
Enterprise-grade with LookML controls
—
Enterprise Compliance Certifications(count)
SOC 2 Type II, ISO 27001, HIPAA, FedRAMP (GCP)
—
Show 1 more attribute
Row-Level Security (RLS) Complexity(capability level)
Advanced contextual RLS with LookML
—
GitHub Community Stars(stars)
Limited public info
—
GitHub Stars (Community Adoption)(stars)
Not open-source
—
Monthly Subscription Cost (Enterprise)(USD)
$3,500 (average)
—
Starting Annual Price(USD)
$5,000 entry-level
—
Minimum Annual Cost (Enterprise)(USD)
$100,000
$70,000
Starting Annual Cost(USD)
$5,000
—
Cost for 100-User Organization (Annual)(USD)
$25,000 - $50,000
—
Show 22 more attributes
Base Annual Cost (Single User)(USD)
$60,000+
—
Starting Price (per user/month)(USD)
$500+ (org-wide minimum)
—
Starting Monthly Cost Per User(USD)
$35
—
Annual License Cost (500 users)(USD)
$400,000-$800,000
—
Starting Enterprise Contract Value(USD per year)
$50,000
$180,000
Average Monthly Cost Per User(USD)
$800-$3,000
—
Starting Price (Annual)(USD)
$24,000
—
Starting Cost (Annual, Single User)(USD)
$24,000-60,000
—
Starting Price Per User (Annual)(USD)
$3,000
—
Base Monthly Cost Per User(USD)
$24/month
—
Annual Cost (100 Users)(USD)
$28,800
—
Starting Annual Cost (Small Org)(USD)
$50,000+
—
Total Cost of Ownership (First Year, 10 Users)(USD)
$6,000-$12,000 (minimum enterprise license)
—
Starting Annual Cost (Single User)(USD)
$2,000
—
Starting Price (Annual, 10 Users)(USD)
$45,000
—
Base Starter Price (Annual)(USD)
$3,000 per core minimum
—
Base Annual Cost Per User(USD)
$2,000 - $5,000
—
Starting Enterprise License(USD annually)
$70,000
—
Starting Monthly Cost (SaaS)(USD)
$2,000
—
Self-Hosting Cost(USD)
Not available
—
Starting User Cost (Annual)(USD per user)
$600-$3,200
—
Typical Mid-Market Annual Contract Value(USD)
$200,000-$500,000
—
AI/Predictive Analytics
Built-in with automated insight discovery
—
Embedded Analytics Capability(null)
Basic (limited white-label)
Purpose-built, highly white-labelable
Mobile App Capability
Native iOS/Android with full features
Web-responsive, limited interactivity
Customization Flexibility (1-10 scale)(score)
6/10 (Visual builders)
9/10 (LookML code control)
AI-Powered Insights
Domo AI with natural language queries
Limited predictive models
Show 14 more attributes
Workflow Automation Capabilities
Advanced (alerts, scheduling, actions)
—
Native Workflow Automation(null)
Yes - alerts, routing, task execution
—
Visualization Types Available(count)
90+
50+ visualizations
Native Mobile App Support(null)
Yes (with offline mode)
—
White-Label Embedding Capability(capability level)
Limited / add-on cost
Enterprise SDK included
Mobile App Functionality(percentage)
95% (with offline mode)
—
Mobile App
Native iOS/Android + responsive web
—
API Capabilities
Advanced GraphQL and REST APIs
—
Embedded Analytics Support(capability score)
Excellent - Native support
—
Enterprise Embedded Analytics Support(tier level)
Native in all plans
—
Visualization Types(count)
80+ chart types
—
Data Sources Supported(integrations)
80+ connectors
—
Available Chart Types(count)
60+ visualization types
—
Custom Modeling Language
LookML (proprietary)
—
Deployment Flexibility
Cloud-only (SaaS)
—
Deployment Options
Cloud (SaaS only)
—
Typical Org Size (Target)(employees)
500+ (enterprise)
—
Average Dashboard Load Time(seconds)
2-3 seconds
—
Query Latency (100M rows)(milliseconds)
<500ms
—
Data Refresh Rate(times per day)
Real-time (unlimited)
—
Query Response Time (10B rows)(seconds)
5-15
—
Maximum Dataset Size (Optimal Performance)(rows)
50M rows
—
Show 9 more attributes
Maximum Recommended Dataset Size(rows)
500 million
10 billion+
Maximum Dataset Size Supported(GB)
500GB+ (with optimization)
—
Query Speed (Caching)(ms)
500-2000
—
Query Performance (Sub-second)(milliseconds)
500-2000ms
—
Maximum Dataset Size (Optimized)(GB)
100+ GB
—
Query Response Time (100GB dataset)(seconds)
2-5 seconds
—
BigQuery Native Optimization(null)
Full automatic caching and pushdown
—
BigQuery Query Speed(milliseconds)
Average 800ms for 100M rows
—
Average Query Response Time(seconds)
3.5 seconds
—
Typical Implementation Time(days)
2-4 weeks
7-14 days
Average Implementation Duration(weeks)
2.5 weeks
8 weeks
Average Implementation Timeline(weeks)
2-4 weeks
10 weeks
Typical Implementation Timeline(weeks)
4-8 months
8-16 weeks
Typical Enterprise Implementation(weeks)
8-16
—
Show 6 more attributes
Typical Implementation Timeline(months)
4-6 months
—
Implementation Timeline(weeks)
18-26 weeks
—
Typical Enterprise Implementation Timeline(weeks)
12 weeks average
—
Cloud Architecture Model(null)
Cloud-native SaaS (single-tenant)
—
Implementation Time (typical)(weeks)
8-12 weeks (requires modeling)
—
Supported Cloud Platforms(count)
1 (Google Cloud native)
—
Maximum Concurrent Users (Standard Plan)(users)
Unlimited (license-based)
—
Maximum Data Model Size(GB)
500 GB (with optimization)
—
Maximum Concurrent Users Supported(users)
Unlimited (cloud-native)
10,000+
Maximum Dashboard Users(per plan)
Unlimited (enterprise)
—
Maximum Concurrent Users(users)
5,000+ users
—
Show 1 more attribute
Max Concurrent Users (Recommended)(users)
100+
—
Free Trial Period(days)
30 days
14 days
Average Implementation Time(days)
4-8 weeks
2-4 weeks
User Adoption Rate (Typical)(percent)
75% within 60 days
—
Mobile App Usability Rating(score out of 10)
8.2/10
—
Setup Time(minutes)
4-8 weeks
—
Mobile App Native Support(capability level)
Web-responsive design, limited mobile
—
Support Tier - Response Time (Premium)(hours)
1 hour
—
Database Query Language Support
SQL via connectors, limited direct database access
Native SQL, complex joins, window functions
Data Connectors Available(count)
700+
800+ (via Fivetran)
Google Workspace Integration
Partial - via connectors
—
Native Excel Integration
Limited, requires API
—
Pre-built Data Connectors(count)
500+
—
Show 10 more attributes
Native Data Connectors Available(count)
70+
—
Native Data Connectors(connectors)
300+
1,000+
Number of Native Data Connectors(count)
600+
250+
Data Connectors(count)
60+
—
Data Connectors Available(count)
200+
—
Native Database Connectors(count)
200+
—
Data Connector Integrations(count)
600+ integrations
—
Data Connectors Supported(count)
70+ connectors
—
Data Source Connectors(count)
300+
—
Number of Native Connectors(connectors)
90+
—
Non-Technical User Friendliness (1-10 scale)(score)
8.5/10 (drag-and-drop design)
5/10 (requires technical knowledge)
Non-Technical User Self-Service Rate(percent)
90%
—
Analyst Proficiency Learning Period(weeks)
2-3 weeks
—
User Interface Complexity Rating(score)
Complex (steep curve)
—
Learning Curve Difficulty(scale 1-10)
7/10 (Steep)
—
Show 4 more attributes
Business User Learning Time(days)
14-21 days
—
Self-Service Analytics Maturity(1-10 scale)
5/10 (requires LookML expertise)
—
Learning Curve (Hours to First Dashboard)(hours)
40-60 hours (with developer background)
—
Learning Curve for Non-Technical Users(hours to first dashboard)
40-80 hours
—
Global Market Share (2025)(percent)
2.4%
—
Global BI Platform Market Share(percent)
11.2%
—
Market Share (2025)(%)
8-10%
—
Global Market Share(%)
12.5%
—
Enterprise Market Share(%)
12%
—
Show 1 more attribute
Enterprise BI Market Share(%)
8-12%
—
Time to Create First Dashboard(hours (for beginner))
20-30
—
Requires SQL/Code Knowledge(boolean)
No, drag-and-drop
—
Percentage of Use Cases Needing Code(percent)
15%
40%
Learning Curve (Days to First Dashboard)(days)
5-10 days
—
Learning Curve Complexity(1–10 scale)
Advanced (requires SQL/LookML)
—
Built-in ETL/Data Integration
Advanced (native)
—
Visualization Customization Level
Good (operational focus)
—
AI/ML Automation Capabilities(score)
Basic (predictive only)
—
Machine Learning / AI Features
Looker Studio, Einstein AI, predictive analytics
—
Mobile App Editing Capability(text)
Full feature parity with desktop
—
Minimum Team Training Required(weeks)
4-6 weeks
—
Mobile Dashboard Editing
Full editing capabilities
—
Built-in Data Governance Tools
Native data certification & lineage
—
Row-Level Security (RLS) Support
Native RLS with attribute-based access
—
Time to First Dashboard(weeks)
0.75 hours
6-12 weeks
G2 Customer Satisfaction Score(out of 5 stars)
4.5/5
—
Real-time Collaboration Features
Built-in
—
Mobile App Store Rating(stars)
4.3/5 (2,400 reviews)
—
Built-in ETL Transformation(yes/no)
Yes (Domo Connector Framework)
—
Starting Price (Monthly per User)(USD)
$500
—
Enterprise Edition Annual Cost per User(USD)
$2,400
—
Global Active Users(millions)
0.15M
—
Mobile App Dashboard Interactivity(capability level)
Full interactivity + alerts
Read-only
Mobile App Completeness(feature parity %)
60% of desktop features
—
Mobile App Quality
4/5 stars
—
API Rate Limit(requests per second)
1,000 RPM
—
Data Model Customization Depth(complexity level)
Advanced (custom dimensions, measures, derived tables)
—
Average Training Hours Required (Per Analyst)(hours)
40-60 hours
—
Semantic Layer Capability
Advanced (LookML semantic layer)
—
Global Active Users (2026)(millions)
1.2+ million
—
Typical User Training Required(hours)
40-80 hours
—
Semantic Layer (Metric Consistency)(null)
Native LookML ensures single source of truth
—
Semantic Layer Strength(governance level)
Built-in (LookML) - single source of truth
—
Centralized Metric Management(text)
LookML semantic layer with version control
—
Time to Deploy First Dashboard(minutes)
14-21 days
—
Semantic Layer Maturity(scale 1-10)
9/10 (centralized LookML)
—
Mobile App Support
Limited; primarily desktop-focused
—
Natural Language Query Capability(text)
Basic Explore interface (code-based)
—
Open Source Availability
Closed source (Google proprietary)
—
Available Data Connectors(integrations)
750+
—
Embedded Analytics Suitability(rating)
Excellent (core platform strength)
—
SQL Modeling Flexibility(capability level)
Unrestricted (LookML + native SQL)
—
Pros & Cons
10 pros·6 cons across both
D
D
Domo
+5-3
Pros
- Intuitive drag-and-drop interface requiring minimal SQL knowledge
- Native mobile app with offline access and push notifications
- Faster deployment (2-4 weeks vs competitor 8-12 weeks average)
- Strong data integration with 1,000+ pre-built connectors
- Superior customer success and training for business users
Cons
- Limited advanced data modeling compared to code-first platforms
- Higher per-user licensing costs ($800-$2,500/user annually)
- Weaker embedded analytics capabilities vs specialized competitors
Looker
+5-3
Pros
- LookML enables enterprise-grade data governance and reusable metrics
- World-class embedded analytics for SaaS and customer-facing applications
- Seamless integration with Google Cloud Platform (BigQuery, Dataflow, etc.)
- Superior row-level security and complex permission matrices
- Strong developer ecosystem with extensive API capabilities
Cons
- Steep learning curve requiring SQL and LookML expertise
- Higher total cost of ownership with required technical staff
- Limited native mobile app functionality vs web experience
Frequently Asked Questions
5 questions
Looker is significantly better for embedded analytics. It was designed specifically for white-label, customer-facing analytics with superior security, branding customization, and programmatic control. Domo's strengths are internal self-service analytics rather than customer-facing embedded use cases. Looker's row-level security and fine-grained permissions make it ideal for multi-tenant SaaS deployments.
Resources & Learn More
Curated sources to dive deeper
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Wikipedia
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