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Statsig Warehouse Native vs Statsig Cloud
Add Statsig to your warehouse for end-to-end experimentation including targeting and feature rollouts with holdouts and layers
Statsig Warehouse Native versus Statsig Cloud
Statsig Cloud
- Statsig hosts your data.
- Suite of SDKs, APIs, and integrations that allow you to manage assignments and log or import events and exposures.
- Feature gates, a wide array of analytics tools, and 1 million metered events for free.
- Suitable for organizations beginning their journey in data-driven experimentation, especially if they are already using other SaaS tools for data and metrics.
Statsig Warehouse Native
- Use Statsig’s Stats Engine within your data warehouse to calculate metric lifts using your pre-existing data sets.
- Use third-party or your own SDKs for feature assignment or opt for Statsig’s SDKs for randomization.
- Ideal for companies that are privacy-sensitive or already have a robust data team and infrastructure in place.
- Integrates with various tools like Snowflake, BigQuery, Segment, Redshift, Databricks, etc., and supports a modular approach, allowing you to choose specific capabilities like assignment or experiment analysis.
- Supports advanced features like multiple unit types, timeseries breakdowns, dimensional breakdowns, custom queries, advanced metrics, and statistical tools.
Compare head-to-head
| Feature/Aspect | Statsig Warehouse Native | Statsig Cloud |
|---|---|---|
| Data Hosting | Data is hosted in your own data warehouse. | Statsig hosts your data. |
| Primary Source of Metrics | Warehouse is the primary source, ideal for using existing data pipelines and computation. | Primary source of metrics comes from Statsig SDKs or CDPs like Segment. |
| Analysis Needs | Flexible analysis on top of existing source of truth metric data. | Automated experimentation for every experiment and product launch, especially with metrics from event logging. |
| Data Team Involvement | Necessary for setting up warehouse connection and configuring core metrics. | Involvement is optional but recommended for experiment design and readouts. |
| Costs | Includes Statsig license plus costs for computation and storage in your warehouse. | Total cost of ownership (TCO) is slightly lower, no warehouse costs involved. |
| Modularity | Modular: Opt for integrated end-to-end platform or select subsets of capabilities. | Integrated end-to-end platform covering SDKs for feature rollout, experiment execution, analysis, and readouts. |
| Integration with Existing Tools | Seamless integration with tools like Snowflake, BigQuery, Segment, Redshift, Databricks, etc. | Synergy with other SaaS tools for customer data and metrics, like Segment. |
| Privacy and Security | Preferable for organizations with stringent data egress policies. | Suitable for organizations with less restrictive data egress policies. |
| Setup Complexity | Requires more initial setup, particularly around data warehouse integration. | Easier setup for developers, less initial configuration required. |
| Experimentation Flexibility | Supports advanced experimentation features using pre-existing data sets. | Provides a reliable method for creating metrics with less engineering effort. |
| SDKs Usage | Use your own or third-party SDKs for feature assignment; also supports Statsig SDKs. | Primarily relies on Statsig SDKs for feature assignment and metrics logging. |
A warehouse-native solution for experimentation and analytics
Run Statsig in your data warehouse to run experiment analysis, analytics
workflows, and more. Build with our infrastructure, or bring your own
solution for assignment
No extra overhead
Bring your existing metric data and exposures. Statsig Warehouse Native
runs seamlessly on top of your existing data, giving you instant
experiment results from the world's most powerful stats engine
Bring your tools, or use our infra
Love your existing assignment and flagging solution? Feel free to keep it.
Otherwise, feel free to leverage our SDK and flagging solution, and write
exposures directly into your warehouse
Analytics just got better
Run all your product analytics workflows within your own data warehouse,
with data that's seamlessly connected to your experiments and releases
