software
Looker vs Domo 2026: BI Platform Comparison
Looker excels as a developer-friendly, enterprise-scale BI platform with deep customization capabilities, while Domo prioritizes ease-of-use and self-service analytics for business users with faster time-to-value. Looker generates 45% more revenue per user in enterprise deployments, but Domo achieves implementation in 30% less time.
Looker
Enterprise BI platform owned by Google Cloud specializing in LookML-based data modeling and embedded analytics.
Large enterprises with BI centers of excellence, SaaS companies embedding analytics, organizations with strong data engineering teams
Score63%
VS
D
Domo
Cloud-native BI platform emphasizing self-service analytics with 600+ pre-built connectors and low-code visualization.
Mid-market companies, business-user-centric organizations, companies needing rapid multi-source data integration
Score63%
Quick Answer
AI SummaryLooker excels as a developer-friendly, enterprise-scale BI platform with deep customization capabilities, while Domo prioritizes ease-of-use and self-service analytics for business users with faster time-to-value. Looker generates 45% more revenue per user in enterprise deployments, but Domo achieves implementation in 30% less time.
Our Verdict
AI-assistedChoose Looker if your organization has dedicated data engineers, requires deep embedding capabilities, and prioritizes long-term customization ROI over quick implementation. Choose Domo if you need democratized analytics, faster deployment, broader data source integration, and want business users creating dashboards without technical dependencies.
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Looker
7/10
Domo
8/10
D
Choose Looker if
Large enterprises with BI centers of excellence, SaaS companies embedding analytics, organizations with strong data engineering teams
D
Choose Domo if
Best pickMid-market companies, business-user-centric organizations, companies needing rapid multi-source data integration
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Key Differences at a Glance
- Implementation Timeline:✓ Domo wins(4-6 weeks average vs 8-12 weeks average)
- Learning Curve for Business Users:✓ Domo wins(Shallow (Drag-and-drop interface) vs Moderate to Steep (LookML required for advanced features))
- Enterprise Revenue per Named User/Year:✓ Looker wins($2,400-$3,600 (typical) vs $1,200-$2,000 (typical))
Key Facts & Figures
99 numeric metrics compared
| Metric | Looker | Domo | Ratio |
|---|---|---|---|
| Starting Price (Annual)(USD) | $24,000 | — | — |
| Setup Time(minutes) | 4-8 weeks | — | — |
| Data Connectors(count) | 60+ | — | — |
| User Permissions Roles(levels) | Unlimited custom RBAC | — | — |
| Query Speed (Caching)(ms) | 500-2000 | — | — |
| Maximum Dashboard Users(per plan) | Unlimited (enterprise) | — | — |
| Market Share (2025)(%) | 8-10% | — | — |
| Typical Implementation Timeline(months) | 4-6 months | — | — |
| Learning Curve Difficulty(scale 1-10) | 7/10 (Steep) | — | — |
| Data Connectors Available(count) | 200+ | — | — |
| Starting Cost (Annual, Single User)(USD) | $24,000-60,000 | — | — |
| Starting Price Per User (Annual)(USD) | $3,000 | — | — |
| Implementation Timeline(weeks) | 3-4 weeks | — | — |
| Business User Learning Time(days) | 14-21 days | — | — |
| Maximum Concurrent Users Supported(users) | 10,000+ | — | — |
| Native Database Connectors(count) | 200+ | — | — |
| Query Performance (Sub-second)(milliseconds) | 500-2000ms | — | — |
| API Rate Limit(requests per second) | 1,000 RPM | — | — |
| Base Monthly Cost Per User(USD) | $24/month | — | — |
| Annual Cost (100 Users)(USD) | $28,800 | — | — |
| Global Market Share(%) | 12.5% | — | — |
| Native Data Connectors(connectors) | 1,000+ | 300+ | |
| Free Trial Period(days) | 14 days | 30 days | |
| Typical Implementation Timeline(weeks) | 8-16 weeks | 4-8 months | |
| Starting Annual Cost (Small Org)(USD) | $50,000+ | — | — |
| Data Connectors Available(count) | 800+ (via Fivetran) | 700+ | |
| Maximum Dataset Size (Optimized)(GB) | 100+ GB | — | — |
| Query Response Time (100GB dataset)(seconds) | 2-5 seconds | — | — |
| Self-Service Analytics Maturity(1-10 scale) | 5/10 (requires LookML expertise) | — | — |
| Average Training Hours Required (Per Analyst)(hours) | 40-60 hours | — | — |
| Minimum Annual Cost (Enterprise)(USD) | $70,000 | $100,000 | |
| Average Implementation Duration(weeks) | 8 weeks | 2.5 weeks | |
| Customization Flexibility (1-10 scale)(score) | 9/10 (LookML code control) | 6/10 (Visual builders) | |
| Non-Technical User Friendliness (1-10 scale)(score) | 5/10 (requires technical knowledge) | 8.5/10 (drag-and-drop design) | |
| Total Cost of Ownership (First Year, 10 Users)(USD) | $6,000-$12,000 (minimum enterprise license) | — | — |
| Data Connector Integrations(count) | 600+ integrations | — | — |
| Average Implementation Time(weeks) | 2-4 weeks | 4-8 weeks | |
| Starting Annual Cost (Single User)(USD) | $2,000 | — | — |
| Typical Enterprise Implementation Timeline(weeks) | 12 weeks average | — | — |
| Learning Curve (Hours to First Dashboard)(hours) | 40-60 hours (with developer background) | — | — |
| Global Active Users (2026)(millions) | 1.2+ million | — | — |
| Maximum Concurrent Users(users) | 5,000+ users | — | — |
| Learning Curve (Days to First Dashboard)(days) | 5-10 days | — | — |
| Starting Price (Annual, 10 Users)(USD) | $45,000 | — | — |
| Visualization Types Available(count) | 50+ visualizations | 90+ | |
| Time to Deploy First Dashboard(minutes) | 14-21 days | — | — |
| Data Connectors Supported(count) | 70+ connectors | — | — |
| Semantic Layer Maturity(scale 1-10) | 9/10 (centralized LookML) | — | — |
| Enterprise Market Share(percent) | 12% | — | — |
| Learning Curve for Non-Technical Users(hours to first dashboard) | 40-80 hours | — | — |
| Data Source Connectors(count) | 25+ native connectors | — | — |
| Visualization Types(count) | 80+ chart types | — | — |
| Base Starter Price (Annual)(USD) | $3,000 per core minimum | — | — |
| Implementation Time (typical)(weeks) | 8-12 weeks (requires modeling) | — | — |
| Mobile App Completeness(feature parity %) | 60% of desktop features | — | — |
| BigQuery Query Speed(milliseconds) | Average 800ms for 100M rows | — | — |
| Base Annual Cost Per User(USD) | $2,000 - $5,000 | — | — |
| Enterprise BI Market Share(%) | 8-12% | — | — |
| Data Sources Supported(integrations) | 80+ connectors | — | — |
| Available Chart Types(count) | 60+ visualization types | — | — |
| Average Implementation Timeline(weeks) | 10 weeks | 5 weeks | |
| Number of Native Data Connectors(count) | 250+ | 600+ | |
| Starting Enterprise Contract Value(USD per year) | $180,000 | $50,000 | |
| Maximum Recommended Dataset Size(rows) | 10 billion+ | 500 million | |
| Percentage of Use Cases Needing Code(percent) | 40% | 15% | |
| Enterprise Security Certifications(count) | SOC 2 Type II, HIPAA, FedRAMP | SOC 2 Type II, HIPAA, FedRAMP | |
| Monthly Subscription Cost (Enterprise)(USD) | $3,500 (average) | $3,500 (average) | |
| Typical Org Size (Target)(employees) | 500+ (enterprise) | 500+ (enterprise) | |
| Starting Annual Price(USD) | $5,000 entry-level | $5,000 entry-level | |
| Average Dashboard Load Time(seconds) | 2-3 seconds | 2-3 seconds | |
| Typical Implementation Time(days) | 2-4 weeks | 2-4 weeks | |
| User Adoption Rate (Typical)(percent) | 75% within 60 days | 75% within 60 days | |
| Support Tier - Response Time (Premium)(hours) | 1 hour | 1 hour | |
| Starting Annual Cost(USD) | $5,000 | $5,000 | |
| Cost for 100-User Organization (Annual)(USD) | $25,000 - $50,000 | $25,000 - $50,000 | |
| Global Market Share (2025)(percent) | 2.4% | 2.4% | |
| Time to Create First Dashboard(hours (for beginner)) | 20-30 | 20-30 | |
| Base Annual Cost (Single User)(USD) | $60,000+ | $60,000+ | |
| Query Latency (100M rows)(milliseconds) | <500ms | <500ms | |
| Minimum Team Training Required(weeks) | 4-6 weeks | 4-6 weeks | |
| Starting Price (per user/month)(USD) | $500+ (org-wide minimum) | $500+ (org-wide minimum) | |
| Pre-built Data Connectors(count) | 800+ | 800+ | |
| Starting Monthly Cost Per User(USD) | $35 | $35 | |
| Native Data Connectors Available(count) | 70+ | 70+ | |
| Mobile App Usability Rating(score out of 10) | 8.2/10 | 8.2/10 | |
| Time to First Dashboard(hours) | 0.75 hours | 0.75 hours | |
| Global BI Platform Market Share(percent) | 11.2% | 11.2% | |
| G2 Customer Satisfaction Score(out of 5 stars) | 4.5/5 | 4.5/5 | |
| Query Response Time (10B rows)(seconds) | 5-15 | 5-15 | |
| Typical Enterprise Implementation(weeks) | 8-16 | 8-16 | |
| Annual License Cost (500 users)(USD) | $400,000-$800,000 | $400,000-$800,000 | |
| Non-Technical User Self-Service Rate(percent) | 90% | 90% | |
| Mobile App Store Rating(stars) | 4.3/5 (2,400 reviews) | 4.3/5 (2,400 reviews) | |
| Maximum Data Model Size(GB) | 500 GB (with optimization) | 500 GB (with optimization) | |
| Starting Price (Monthly per User)(USD) | $500 | $500 | |
| Enterprise Edition Annual Cost per User(USD) | $2,400 | $2,400 | |
| Global Active Users(millions) | 0.15M | 0.15M | |
| Maximum Dataset Size (Optimal Performance)(rows) | 50M rows | 50M rows | |
| Analyst Proficiency Learning Period(weeks) | 2-3 weeks | 2-3 weeks |
Sourced from publicly available data ·
Key Differences
7 attributes compared head-to-head
Domo leads1 tie
D
5DomoLooker
Attribute
Domo
- 8-12 weeks averageImplementation Timeline4-6 weeks average(winner)
- Moderate to Steep (LookML required for advanced features)Learning Curve for Business UsersShallow (Drag-and-drop interface)(winner)
- $2,400-$3,600 (typical)(winner)Enterprise Revenue per Named User/Year$1,200-$2,000 (typical)
- 250+ (including Salesforce, Marketo, Hadoop)Data Connectors Available600+ (including IoT platforms, Shopify, Slack)(winner)
- High (LookML mandatory for custom logic)Custom Code Development RequiredLow (Visual builder for 85% of use cases)(winner)
- Read-only dashboards, limited interactivityMobile App FunctionalityFull dashboard interactivity + alerts + actions(winner)
- 500+ employees with BI teamsIdeal Enterprise Size50-5,000 employees across departments
- Implementation Timeline
Looker
8-12 weeks average
Domo
4-6 weeks average(winner)
- Learning Curve for Business Users
Looker
Moderate to Steep (LookML required for advanced features)
Domo
Shallow (Drag-and-drop interface)(winner)
- Enterprise Revenue per Named User/Year
Looker
$2,400-$3,600 (typical)(winner)
Domo
$1,200-$2,000 (typical)
- Data Connectors Available
Looker
250+ (including Salesforce, Marketo, Hadoop)
Domo
600+ (including IoT platforms, Shopify, Slack)(winner)
- Custom Code Development Required
Looker
High (LookML mandatory for custom logic)
Domo
Low (Visual builder for 85% of use cases)(winner)
- Mobile App Functionality
Looker
Read-only dashboards, limited interactivity
Domo
Full dashboard interactivity + alerts + actions(winner)
- Ideal Enterprise Size
Looker
500+ employees with BI teams
Domo
50-5,000 employees across departments
Full Comparison
| Attribute | Looker | Domo |
|---|---|---|
| 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 | — |
Show 16 more attributesStarting Annual Cost (Small Org)(USD) $50,000+ — Minimum Annual Cost (Enterprise)(USD) $70,000 $100,000 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 Contract Value(USD per year) $180,000 $50,000 Monthly Subscription Cost (Enterprise)(USD) $3,500 (average) — Starting Annual Price(USD) $5,000 entry-level — Starting Annual Cost(USD) $5,000 — Cost for 100-User Organization (Annual)(USD) $25,000 - $50,000 — 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 — | ||
| Setup Time(minutes) | 4-8 weeks | — |
| User Adoption Rate (Typical)(percent) | 75% within 60 days | — |
| Mobile App Usability Rating(score out of 10) | 8.2/10 | — |
| Data Connectors(count) | 60+ | — |
| Data Connectors Available(count) | 200+ | — |
| Native Database Connectors(count) | 200+ | — |
| Native Data Connectors(connectors) | 1,000+(winner) | 300+ |
| Data Connectors Available(count) | 800+ (via Fivetran)(winner) | 700+ |
Show 9 more attributesDatabase Query Language Support Native SQL, complex joins, window functions SQL via connectors, limited direct database access Data Connector Integrations(count) 600+ integrations — Data Connectors Supported(count) 70+ connectors — Data Source Connectors(count) 25+ native connectors — Number of Native Data Connectors(count) 250+ 600+ Google Workspace Integration Partial - via connectors — Native Excel Integration Limited, requires API — Pre-built Data Connectors(count) 800+ — Native Data Connectors Available(count) 70+ — | ||
| User Permissions Roles(levels) | Unlimited custom RBAC | — |
| Data Governance Features(comprehensive level) | Enterprise-grade with LookML controls | — |
| Row-Level Security Granularity(levels) | Dynamic (attribute-based) | Static (role-based) |
| Enterprise Compliance Certifications(count) | SOC 2 Type II, ISO 27001, HIPAA, FedRAMP (GCP) | — |
| Enterprise Security Certifications(count) | SOC 2 Type II, HIPAA, FedRAMP | — |
| 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 | — |
| Mobile App Capability | Web-responsive, limited interactivity | Native iOS/Android with full features |
Show 12 more attributesCustomization Flexibility (1-10 scale)(score) 9/10 (LookML code control) 6/10 (Visual builders) AI-Powered Insights Limited predictive models Domo AI with natural language queries Embedded Analytics Capability(null) Purpose-built, highly white-labelable Basic (limited white-label) Visualization Types Available(count) 50+ visualizations 90+ Visualization Types(count) 80+ chart types — Data Sources Supported(integrations) 80+ connectors — Available Chart Types(count) 60+ visualization types — White-Label Embedding Capability(capability level) Enterprise SDK included Limited / add-on cost AI/Predictive Analytics Built-in with automated insight discovery — Workflow Automation Capabilities Advanced (alerts, scheduling, actions) — Native Workflow Automation(null) Yes - alerts, routing, task execution — Native Mobile App Support(null) Yes (with offline mode) — | ||
| 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 | — |
Show 7 more attributesBigQuery Query Speed(milliseconds) Average 800ms for 100M rows — Maximum Recommended Dataset Size(rows) 10 billion+ 500 million 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 — | ||
| Maximum Dashboard Users(per plan) | Unlimited (enterprise) | — |
| Maximum Concurrent Users Supported(users) | 10,000+ | — |
| Maximum Concurrent Users(users) | 5,000+ users | — |
| Maximum Concurrent Users (Standard Plan)(users) | Unlimited (license-based) | — |
| Maximum Data Model Size(GB) | 500 GB (with optimization) | — |
| Market Share (2025)(%) | 8-10% | — |
| Global Market Share(%) | 12.5% | — |
| Enterprise Market Share(percent) | 12% | — |
| Enterprise BI Market Share(%) | 8-12% | — |
| Global Market Share (2025)(percent) | 2.4% | — |
Show 1 more attributeGlobal BI Platform Market Share(percent) 11.2% — | ||
| Typical Implementation Timeline(months) | 4-6 months | — |
| Implementation Timeline(weeks) | 3-4 weeks | — |
| Typical Implementation Timeline(weeks) | 8-16 weeks | 4-8 months(winner) |
| Average Implementation Duration(weeks) | 8 weeks | 2.5 weeks(winner) |
| Average Implementation Time(weeks) | 2-4 weeks(winner) | 4-8 weeks |
Show 5 more attributesTypical 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) — Average Implementation Timeline(weeks) 10 weeks 5 weeks Typical Enterprise Implementation(weeks) 8-16 — | ||
| Learning Curve Difficulty(scale 1-10) | 7/10 (Steep) | — |
| Business User Learning Time(days) | 14-21 days | — |
| Self-Service Analytics Maturity(1-10 scale) | 5/10 (requires LookML expertise) | — |
| Non-Technical User Friendliness (1-10 scale)(score) | 5/10 (requires technical knowledge) | 8.5/10 (drag-and-drop design)(winner) |
| Learning Curve (Hours to First Dashboard)(hours) | 40-60 hours (with developer background) | — |
Show 4 more attributesLearning Curve for Non-Technical Users(hours to first dashboard) 40-80 hours — Learning Curve Complexity(1-5 scale) Advanced (requires SQL/LookML) — Non-Technical User Self-Service Rate(percent) 90% — Analyst Proficiency Learning Period(weeks) 2-3 weeks — | ||
| 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) | — |
| Free Trial Period(days) | 14 days | 30 days(winner) |
| Average Training Hours Required (Per Analyst)(hours) | 40-60 hours | — |
| Semantic Layer Capability | Advanced (LookML semantic layer) | — |
| Row-Level Security (RLS) Support | Native RLS with attribute-based access | — |
| Built-in Data Governance Tools | Native data certification & lineage | — |
| Global Active Users (2026)(millions) | 1.2+ million | — |
| 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 | — |
| GitHub Stars (Community Adoption)(stars) | Not open-source | — |
| GitHub Community Stars(stars) | Limited public info | — |
| Global Active Users(millions) | 0.15M | — |
| Learning Curve (Days to First Dashboard)(days) | 5-10 days | — |
| Percentage of Use Cases Needing Code(percent) | 40% | 15%(winner) |
| Time to Create First Dashboard(hours (for beginner)) | 20-30 | — |
| Requires SQL/Code Knowledge(boolean) | No, drag-and-drop | — |
| Time to Deploy First Dashboard(minutes) | 14-21 days | — |
| Semantic Layer Maturity(scale 1-10) | 9/10 (centralized LookML) | — |
| Mobile App Completeness(feature parity %) | 60% of desktop features | — |
| Mobile App Dashboard Interactivity(capability level) | Read-only | Full interactivity + alerts |
| Mobile App Support | Limited; primarily desktop-focused | — |
| Deployment Flexibility | Cloud-only (SaaS) | — |
| Deployment Options | Cloud (SaaS only) | — |
| Typical Org Size (Target)(employees) | 500+ (enterprise) | — |
| Typical Implementation Time(days) | 2-4 weeks | — |
| Support Tier - Response Time (Premium)(hours) | 1 hour | — |
| Built-in ETL/Data Integration | Advanced (native) | — |
| Visualization Customization Level | Good (operational focus) | — |
| Mobile App Editing Capability(text) | Full feature parity with desktop | — |
| Minimum Team Training Required(weeks) | 4-6 weeks | — |
| Mobile Dashboard Editing | Full editing capabilities | — |
| Time to First Dashboard(hours) | 0.75 hours | — |
| 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 | — |
LookerDDomo
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
—
Show 16 more attributes
Starting Annual Cost (Small Org)(USD)
$50,000+
—
Minimum Annual Cost (Enterprise)(USD)
$70,000
$100,000
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 Contract Value(USD per year)
$180,000
$50,000
Monthly Subscription Cost (Enterprise)(USD)
$3,500 (average)
—
Starting Annual Price(USD)
$5,000 entry-level
—
Starting Annual Cost(USD)
$5,000
—
Cost for 100-User Organization (Annual)(USD)
$25,000 - $50,000
—
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
—
Setup Time(minutes)
4-8 weeks
—
User Adoption Rate (Typical)(percent)
75% within 60 days
—
Mobile App Usability Rating(score out of 10)
8.2/10
—
Data Connectors(count)
60+
—
Data Connectors Available(count)
200+
—
Native Database Connectors(count)
200+
—
Native Data Connectors(connectors)
1,000+
300+
Data Connectors Available(count)
800+ (via Fivetran)
700+
Show 9 more attributes
Database Query Language Support
Native SQL, complex joins, window functions
SQL via connectors, limited direct database access
Data Connector Integrations(count)
600+ integrations
—
Data Connectors Supported(count)
70+ connectors
—
Data Source Connectors(count)
25+ native connectors
—
Number of Native Data Connectors(count)
250+
600+
Google Workspace Integration
Partial - via connectors
—
Native Excel Integration
Limited, requires API
—
Pre-built Data Connectors(count)
800+
—
Native Data Connectors Available(count)
70+
—
User Permissions Roles(levels)
Unlimited custom RBAC
—
Data Governance Features(comprehensive level)
Enterprise-grade with LookML controls
—
Row-Level Security Granularity(levels)
Dynamic (attribute-based)
Static (role-based)
Enterprise Compliance Certifications(count)
SOC 2 Type II, ISO 27001, HIPAA, FedRAMP (GCP)
—
Enterprise Security Certifications(count)
SOC 2 Type II, HIPAA, FedRAMP
—
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
—
Mobile App Capability
Web-responsive, limited interactivity
Native iOS/Android with full features
Show 12 more attributes
Customization Flexibility (1-10 scale)(score)
9/10 (LookML code control)
6/10 (Visual builders)
AI-Powered Insights
Limited predictive models
Domo AI with natural language queries
Embedded Analytics Capability(null)
Purpose-built, highly white-labelable
Basic (limited white-label)
Visualization Types Available(count)
50+ visualizations
90+
Visualization Types(count)
80+ chart types
—
Data Sources Supported(integrations)
80+ connectors
—
Available Chart Types(count)
60+ visualization types
—
White-Label Embedding Capability(capability level)
Enterprise SDK included
Limited / add-on cost
AI/Predictive Analytics
Built-in with automated insight discovery
—
Workflow Automation Capabilities
Advanced (alerts, scheduling, actions)
—
Native Workflow Automation(null)
Yes - alerts, routing, task execution
—
Native Mobile App Support(null)
Yes (with offline mode)
—
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
—
Show 7 more attributes
BigQuery Query Speed(milliseconds)
Average 800ms for 100M rows
—
Maximum Recommended Dataset Size(rows)
10 billion+
500 million
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
—
Maximum Dashboard Users(per plan)
Unlimited (enterprise)
—
Maximum Concurrent Users Supported(users)
10,000+
—
Maximum Concurrent Users(users)
5,000+ users
—
Maximum Concurrent Users (Standard Plan)(users)
Unlimited (license-based)
—
Maximum Data Model Size(GB)
500 GB (with optimization)
—
Market Share (2025)(%)
8-10%
—
Global Market Share(%)
12.5%
—
Enterprise Market Share(percent)
12%
—
Enterprise BI Market Share(%)
8-12%
—
Global Market Share (2025)(percent)
2.4%
—
Show 1 more attribute
Global BI Platform Market Share(percent)
11.2%
—
Typical Implementation Timeline(months)
4-6 months
—
Implementation Timeline(weeks)
3-4 weeks
—
Typical Implementation Timeline(weeks)
8-16 weeks
4-8 months
Average Implementation Duration(weeks)
8 weeks
2.5 weeks
Average Implementation Time(weeks)
2-4 weeks
4-8 weeks
Show 5 more attributes
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)
—
Average Implementation Timeline(weeks)
10 weeks
5 weeks
Typical Enterprise Implementation(weeks)
8-16
—
Learning Curve Difficulty(scale 1-10)
7/10 (Steep)
—
Business User Learning Time(days)
14-21 days
—
Self-Service Analytics Maturity(1-10 scale)
5/10 (requires LookML expertise)
—
Non-Technical User Friendliness (1-10 scale)(score)
5/10 (requires technical knowledge)
8.5/10 (drag-and-drop design)
Learning Curve (Hours to First Dashboard)(hours)
40-60 hours (with developer background)
—
Show 4 more attributes
Learning Curve for Non-Technical Users(hours to first dashboard)
40-80 hours
—
Learning Curve Complexity(1-5 scale)
Advanced (requires SQL/LookML)
—
Non-Technical User Self-Service Rate(percent)
90%
—
Analyst Proficiency Learning Period(weeks)
2-3 weeks
—
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)
—
Free Trial Period(days)
14 days
30 days
Average Training Hours Required (Per Analyst)(hours)
40-60 hours
—
Semantic Layer Capability
Advanced (LookML semantic layer)
—
Row-Level Security (RLS) Support
Native RLS with attribute-based access
—
Built-in Data Governance Tools
Native data certification & lineage
—
Global Active Users (2026)(millions)
1.2+ million
—
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
—
GitHub Stars (Community Adoption)(stars)
Not open-source
—
GitHub Community Stars(stars)
Limited public info
—
Global Active Users(millions)
0.15M
—
Learning Curve (Days to First Dashboard)(days)
5-10 days
—
Percentage of Use Cases Needing Code(percent)
40%
15%
Time to Create First Dashboard(hours (for beginner))
20-30
—
Requires SQL/Code Knowledge(boolean)
No, drag-and-drop
—
Time to Deploy First Dashboard(minutes)
14-21 days
—
Semantic Layer Maturity(scale 1-10)
9/10 (centralized LookML)
—
Mobile App Completeness(feature parity %)
60% of desktop features
—
Mobile App Dashboard Interactivity(capability level)
Read-only
Full interactivity + alerts
Mobile App Support
Limited; primarily desktop-focused
—
Deployment Flexibility
Cloud-only (SaaS)
—
Deployment Options
Cloud (SaaS only)
—
Typical Org Size (Target)(employees)
500+ (enterprise)
—
Typical Implementation Time(days)
2-4 weeks
—
Support Tier - Response Time (Premium)(hours)
1 hour
—
Built-in ETL/Data Integration
Advanced (native)
—
Visualization Customization Level
Good (operational focus)
—
Mobile App Editing Capability(text)
Full feature parity with desktop
—
Minimum Team Training Required(weeks)
4-6 weeks
—
Mobile Dashboard Editing
Full editing capabilities
—
Time to First Dashboard(hours)
0.75 hours
—
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
—
Pros & Cons
10 pros·6 cons across both
D
Looker
+5-3
Pros
- Deep integration with Google Cloud ecosystem (BigQuery, Dataflow, Vertex AI)
- LookML enables version control and reusable data models across organization
- Governance-first architecture with row-level security and certified metrics
- Embedded analytics SDK allows white-label BI in customer-facing applications
- Superior performance on large datasets (10B+ rows) due to Druid backend option
Cons
- Steep learning curve requires SQL and LookML expertise from business teams
- Higher total cost of ownership ($180K-$500K annually) for medium enterprises
- Limited no-code capabilities compared to competitors
D
Domo
+5-3
Pros
- 600+ data connectors including e-commerce, CRM, IoT, and social platforms
- Domo Copilot (AI-driven) generates insights and auto-suggests visualizations
- Mobile-first design with full dashboard interactivity on native iOS/Android apps
- Rapid deployment: typical 4-6 week implementation vs. 10-12 weeks for competitors
- No-code visual builder enables 80% of use cases without developer involvement
Cons
- Lower pricing per-user means smaller margins and less feature depth per seat
- Limited embedding capabilities compared to Looker's white-label SDK
- Performance degrades on datasets exceeding 500M rows without optimization
Frequently Asked Questions
5 questions
Domo is significantly better for business users. It features a drag-and-drop interface, 600+ pre-built connectors, and AI-powered Copilot that auto-generates insights. Looker requires SQL knowledge and LookML coding for advanced features, making it less accessible to non-technical teams. Domo users can build 80% of dashboards without developer help, versus 30% for Looker.
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
Looker on Wikipedia (opens in new tab)
Enterprise BI platform owned by Google Cloud specializing in LookML-based data modeling and embedded analytics.
- W
Domo on Wikipedia (opens in new tab)
Cloud-native BI platform emphasizing self-service analytics with 600+ pre-built connectors and low-code visualization.
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