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.
Domo vs Looker — Side-by-side comparison on A Versus B
Cloud-native BI platform focused on self-service analytics and business user empowerment.
Google-owned business intelligence platform built on a semantic data layer (LookML) for enterprise data governance.
Primary Use Case. Data Modeling Approach. Implementation Complexity. Mobile Experience. Typical Annual Cost (Mid-Market). White-Label/Embedded Capability. Enterprise Client Base
Choose 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.
Domo: SOC 2 Type II, HIPAA, FedRAMP | Looker: N/A
Domo: Built-in with automated insight discovery | Looker: N/A
Domo: Basic (limited white-label) | Looker: Purpose-built, highly white-labelable
Maximum Concurrent Users (Standard Plan)
Domo: Unlimited (license-based) | Looker: N/A
Domo: Native iOS/Android with full features | Looker: Web-responsive, limited interactivity
Domo: 6/10 (Visual builders) | Looker: 9/10 (LookML code control)
Domo: Domo AI with natural language queries | Looker: Limited predictive models
Domo: SQL via connectors, limited direct database access | Looker: Native SQL, complex joins, window functions
Non-Technical User Friendliness (1-10 scale)
Domo: 8.5/10 (drag-and-drop design) | Looker: 5/10 (requires technical knowledge)
Domo: Advanced (alerts, scheduling, actions) | Looker: N/A
Domo: Good (operational focus) | Looker: N/A
Domo: Full feature parity with desktop | Looker: N/A
Domo: Yes - alerts, routing, task execution | Looker: N/A
Domo: Partial - via connectors | Looker: N/A
Domo: $500+ (org-wide minimum) | Looker: N/A
Domo: Real-time (unlimited) | Looker: N/A
Domo: Limited, requires API | Looker: N/A
Domo: Full editing capabilities | Looker: N/A
Domo: Native data certification & lineage | Looker: N/A
Domo: 4.3/5 (2,400 reviews) | Looker: N/A
Domo: 500 GB (with optimization) | Looker: N/A
Domo: Yes (Domo Connector Framework) | Looker: N/A
Maximum Dataset Size (Optimal Performance)
Domo: Yes (with offline mode) | Looker: N/A
Domo: Full interactivity + alerts | Looker: Read-only
Domo: Limited / add-on cost | Looker: Enterprise SDK included
Domo: Static (role-based) | Looker: Field, row, and dashboard-level
Domo: Unlimited (cloud-native) | Looker: 10,000+
Domo: Basic (predictive only) | Looker: N/A
Domo: 500GB+ (with optimization) | Looker: N/A
Domo: Complex (steep curve) | Looker: N/A
Domo: 95% (with offline mode) | Looker: N/A
Domo: N/A | Looker: Unlimited custom RBAC
Domo: N/A | Looker: Native iOS/Android + responsive web
Domo: N/A | Looker: Advanced GraphQL and REST APIs
Domo: N/A | Looker: Unlimited (enterprise)
Domo: N/A | Looker: Excellent - Native support
Domo: N/A | Looker: Enterprise-grade with LookML controls
Domo: N/A | Looker: Advanced (custom dimensions, measures, derived tables)
Domo: N/A | Looker: 5/10 (requires LookML expertise)
Domo: N/A | Looker: SOC 2 Type II, ISO 27001, HIPAA, FedRAMP (GCP)
Average Training Hours Required (Per Analyst)
Total Cost of Ownership (First Year, 10 Users)
Domo: N/A | Looker: $6,000-$12,000 (minimum enterprise license)
Domo: N/A | Looker: Advanced (LookML semantic layer)
Domo: N/A | Looker: Native RLS with attribute-based access
Typical Enterprise Implementation Timeline
Domo: N/A | Looker: Full automatic caching and pushdown
Learning Curve (Hours to First Dashboard)
Domo: N/A | Looker: 40-60 hours (with developer background)
Domo: N/A | Looker: Native LookML ensures single source of truth
Learning Curve (Days to First Dashboard)
Domo: N/A | Looker: 9/10 (centralized LookML)
Domo: N/A | Looker: Cloud-native SaaS (single-tenant)
Domo: N/A | Looker: $3,000 per core minimum
Domo: N/A | Looker: 8-12 weeks (requires modeling)
Domo: N/A | Looker: Advanced (requires SQL/LookML)
Domo: N/A | Looker: 60% of desktop features
Domo: N/A | Looker: Built-in (LookML) - single source of truth
Domo: N/A | Looker: Average 800ms for 100M rows
Domo: N/A | Looker: 60+ visualization types
Domo: N/A | Looker: LookML semantic layer with version control
Domo: N/A | Looker: Limited; primarily desktop-focused
Domo: N/A | Looker: 1 (Google Cloud native)
Domo: N/A | Looker: Basic Explore interface (code-based)
Domo: N/A | Looker: Looker Studio, Einstein AI, predictive analytics
Domo: N/A | Looker: LookML (proprietary)
Domo: N/A | Looker: Closed source (Google proprietary)
Domo: N/A | Looker: Web-responsive design, limited mobile
Domo: N/A | Looker: Advanced contextual RLS with LookML
Domo: N/A | Looker: Excellent (core platform strength)
Domo: N/A | Looker: Unrestricted (LookML + native SQL)
Typical Mid-Market Annual Contract Value
Domo: N/A | Looker: Robust (LookML-based)
Domo: N/A | Looker: Basic dashboards only
Domo: N/A | Looker: Data engineers & governance
Domo vs Looker — Structured Comparison Data
Machine-readable comparison dataset for Domo vs Looker. Contains 172 attribute comparisons, 5 FAQ pairs.
Domo vs Looker — Attribute Category Vocabulary
Taxonomy of attribute categories used to classify comparison data for Domo vs Looker.
Which platform is better for embedded analytics in a SaaS product?
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.
Can non-technical business users work independently with both platforms?
Yes, but Domo is far more business-user friendly. Domo's drag-and-drop interface allows marketing managers, analysts, and executives to create dashboards without SQL knowledge in 2-4 weeks. Looker requires either analytics engineers or lengthy training for non-technical users due to LookML, making it less suitable for self-service scenarios. If democratizing analytics to business users is priority, Domo wins decisively.
How does pricing scale for enterprise deployments with 500+ users?
Both platforms offer volume discounts at scale, but pricing models differ. Domo typically charges $800-$2,500 per user annually; Looker charges $600-$3,200. For 500 users, Domo averages $225k-$300k/year; Looker $300k-$500k/year, but Looker's per-user cost may decrease more aggressively at 1,000+ users. Looker often requires dedicated technical staff (adding $200k+ salary), making total cost of ownership significantly higher.
Which integrates better with cloud data warehouses like BigQuery, Snowflake, or Redshift?
Both support all major cloud warehouses. However, Looker has a native integration advantage with Google BigQuery (owned by same parent company) with direct SQL push-down and optimized query performance. Domo integrates equally well with Snowflake and Redshift but doesn't have the same optimization advantage with BigQuery. For Snowflake/Redshift-heavy organizations, both are equally strong; for BigQuery-first, Looker has a slight edge.
What's the learning curve difference for analytics teams?
Domo: 2-4 weeks for business users to create simple dashboards; SQL knowledge optional. Looker: 6-12 weeks for SQL-fluent developers to master LookML; requires strong data engineering background. If you need rapid adoption across non-technical teams, Domo wins. If you want a centralized metrics layer maintained by a dedicated analytics engineering team, Looker's LookML approach provides better long-term governance at the cost of steeper initial learning.
Primary Use Case: Domo has Self-service business analytics & dashboards, while Looker has Embedded analytics & data modeling.
Data Modeling Approach: Domo has Visual/UI-based with limited SQL control, while Looker has LookML (proprietary language) with full SQL flexibility.
Implementation Complexity: Domo has 2-4 weeks (business-user friendly), while Looker has 4-12 weeks (requires technical expertise).
Mobile Experience: Domo has Native mobile app with offline capabilities, while Looker has Web-responsive, limited native mobile features.
Consider: Typical Annual Cost (Mid-Market)
Typical Annual Cost (Mid-Market): Domo has $150,000-$300,000, while Looker has $200,000-$500,000.
Consider: White-Label/Embedded Capability
White-Label/Embedded Capability: Domo has Limited, not primary strength, while Looker has Excellent, core strength with full branding control.
Enterprise Client Base: Domo has Mid-market to enterprise (500+ employees), while Looker has Large enterprises (5,000+ employees).