Compare Grafana and Evidence on pricing, features, platforms, and ratings — both Business Intelligence tools, Freemium (Open Source plus Usage-based Cloud) vs…
At a Glance
Grafana
Evidence
Primary category
Business Intelligence
Business Intelligence
Rating
Not documented
Not documented
Pricing model
Freemium (Open Source plus Usage-based Cloud)
Open Source / Freemium
Starting price
Free (self-hosted OSS or Grafana Cloud free tier)
Free (self-hosted); Evidence Cloud from $15/user/month
Free plan
Yes
Yes
Free trial
Not documented
Not documented
Platforms
Web
Web
Team collaboration
Not documented
Not documented
AI features
Yes
Yes
Public API
Yes
Yes
Pricing Compared
Starting price reflects the lowest paid tier, not the full cost for every team size or usage level.
Grafana
Open Source (Self-Hosted) — Free N/A
Cloud Free — Free Monthly
Cloud Pro — From $19/month plus usage Monthly
Cloud Advanced — From $55/month Monthly
Enterprise — Custom (from around $25,000/year) Annual
Evidence
Open Source (Self-Hosted) — Free N/A
Team — $15/user/month monthly
Pro — $25/user/month monthly
Enterprise — Custom annual (quote-based)
Pros & Cons
Grafana
Pros
Free and open source core with no vendor lock-in to a single data store
Connects to virtually any metrics, logs or trace data source in one interface
Highly customizable dashboards backed by a large community plugin ecosystem
Usage-based Cloud pricing can be more cost-effective at scale than closed observability suites
Cons
Usage-based Cloud pricing can become unpredictable for high-cardinality metrics
Self-hosting the full LGTM stack requires meaningful operational expertise
Some advanced features like SSO and premium connectors require Enterprise licensing
PromQL, LogQL and TraceQL have a learning curve for newcomers
Evidence
Pros
Reports are version-controlled as code, enabling Git-based review, diffing, and deployment workflows familiar to engineering teams
Free and open source to self-host with no artificial feature limits on the core framework
Templated pages eliminate manual duplication when building many similar reports across regions, products, or customers
Designed for embedding analytics into customer-facing products, not just internal dashboards
Cons
Requires comfort writing SQL and Markdown; not accessible to non-technical business users who want pure drag-and-drop reporting
Smaller ecosystem and community than established BI incumbents like Tableau, Looker, or Power BI
Evidence Cloud pricing is per-user, which can add up for larger analytics teams
AI features are metered via credits, adding a variable cost dimension beyond the base subscription
Use Cases
Grafana
Infrastructure and Kubernetes Monitoring — Visualize cluster health, resource usage and application metrics collected by Prometheus and other exporters.
Business and Executive Reporting Dashboards — Combine data from SQL databases, APIs and cloud services into shareable business dashboards.
IoT and Sensor Data Visualization — Monitor time-series data streaming from industrial sensors, devices and edge deployments.
Evidence
Internal analytics for lean data teams — A small analytics engineering team builds and maintains a full internal reporting suite using the same Git workflow they already use for data pipeline code.
Customer-facing embedded analytics — A SaaS company embeds Evidence-built reports directly into its product to give customers self-service analytics without building a custom dashboard from scratch.
Automated multi-entity reporting — An organization uses templated pages to automatically generate a separate performance report for every region, store, or account from a single report definition.