Omni Analytics pricing guide details
Pricing Overview
Omni Analytics uses a quote-based enterprise pricing model with no publicly listed prices. The platform offers a free trial so teams can evaluate the product before committing to a contract. To get a custom quote, you need to request a demo through the Omni website and work with their sales team to scope a plan that fits your organization's data infrastructure and user count.
This approach is common among enterprise BI platforms that tailor pricing to factors like the number of users, data warehouse connections, embedded analytics usage, and compliance requirements (SOC 2, HIPAA, GDPR). Omni does not publish tiered pricing or per-seat rates on its website, so all pricing details come from direct negotiation with their team.
Plan Comparison
Because Omni Analytics does not publish specific plan tiers, we cannot provide a side-by-side comparison of named plans with fixed prices. Based on how the platform is positioned and what we know from its feature set, here is what to expect when scoping a deal:
| Feature Area | What Omni Offers |
|---|---|
| Core BI | Dashboards, point-and-click exploration, SQL IDE, spreadsheet-style analysis |
| AI Analytics | Natural language querying, agentic AI, AI-driven forecasting |
| Semantic Model | Centralized metric definitions, reusable logic across deployments |
| Embedded Analytics | White-label embedding, SSO, APIs, MCP server |
| Developer Tools | Git version control, CI/CD, branch mode, testing environments |
| Security & Compliance | Role-based access, audit logs, SOC 2, HIPAA, GDPR |
| Data Connections | Snowflake, BigQuery, Databricks, Redshift, Postgres, ClickHouse, MySQL, Trino, MotherDuck, dbt |
When evaluating quotes, we recommend asking the Omni sales team to clarify whether pricing scales by named user count, concurrent user count, or query volume. Embedded analytics and AI features may carry separate pricing components depending on your deployment model.
Hidden Costs and Considerations
While Omni Analytics bundles a wide set of capabilities into its platform, several cost factors deserve attention before signing a contract:
Data warehouse compute costs. Omni connects directly to your cloud data warehouse (Snowflake, BigQuery, Databricks, etc.). The queries your team runs through Omni generate compute charges on the warehouse side. For organizations with heavy ad-hoc query patterns or large user bases, these costs can exceed the platform license itself.
Embedded analytics scaling. If you plan to use Omni for customer-facing embedded analytics, the pricing may scale with the number of end users or embedded instances. Companies like Standard Metrics and Uscreen have built customer-facing products on Omni, but the cost structure for high-volume embedded use cases should be negotiated upfront.
Implementation and onboarding. Building a semantic model that captures your organization's metric definitions takes real effort. While Omni touts fast deployment (case studies cite 2 weeks to 3 months), the internal time investment from your data team to define metrics, set up governance, and train users is a cost that does not appear on the invoice.
Contract terms and minimums. Enterprise BI contracts typically involve annual commitments with minimum seat counts. We recommend negotiating flexible terms, especially if your team size is growing or you are uncertain about adoption rates.
AI feature availability. Omni is actively shipping new AI capabilities (dashboard generation from prompts, forecasting, agentic workflows). Confirm which AI features are included in your contract versus which may require add-ons or are still in beta.
How Omni Analytics Pricing Compares
Since Omni Analytics does not publish prices, we compare its pricing model against three competitors in the business intelligence category that do share pricing details.
| Platform | Pricing Model | Starting Price | Free Option |
|---|---|---|---|
| Omni Analytics | Enterprise (quote-based) | Contact sales | Free trial |
| Amazon QuickSight | Usage-based | $3/user/mo for Readers and $24 for Authors (Standard) | no published free tier) |
| KNIME | Open source + paid tiers | $19/mo | Free (personal use) |
| Amplitude | Freemium | Plus from $0, scaling with events | Free tier |
Omni Analytics vs. Amazon QuickSight. QuickSight offers transparent per-user pricing starting at $3/user/mo for Readers and $24 for Authors for the Standard plan, with a no published free tier. QuickSight is tightly integrated with the AWS ecosystem, making it a natural choice for AWS-centric organizations. Omni differentiates with its semantic model, AI-powered natural language querying, and stronger embedded analytics capabilities. For teams that need a shared metric layer and AI-driven self-service, Omni offers more depth, but expect a higher price point given the enterprise model.
Omni Analytics vs. KNIME. KNIME takes a fundamentally different approach as an open-source analytics platform with paid tiers starting at $19/month. KNIME is built for data science workflows and automation rather than business intelligence dashboards. If your primary need is interactive BI with AI chat and embedded analytics, Omni is the better fit. KNIME serves teams focused on ETL pipelines, machine learning, and data transformation at a much lower price point.
Omni Analytics vs. Amplitude. Amplitude focuses on product analytics with a freemium model starting at from $0, scaling with eventsnth for the Plus plan. It excels at tracking user behavior, funnels, and product metrics. Omni is a broader BI platform that connects to your data warehouse and supports dashboards, SQL, spreadsheets, and embedded analytics. If you need product-specific analytics, Amplitude is purpose-built for that. If you need a unified analytics layer across business and product data, Omni provides more flexibility.
The bottom line. Omni Analytics positions itself as a premium BI platform with AI capabilities, a semantic model, and embedded analytics support. Organizations evaluating Omni should expect pricing above the self-serve tools listed here, but the platform consolidates capabilities that might otherwise require multiple tools. Request a demo and negotiate based on your specific user count, data warehouse setup, and embedded analytics requirements to get the most accurate pricing picture.