Platform
Developers
Resources
KEY FEATURES
GETTING STARTED
Documentation
Documentation to get you started with implementation
Walkthrough Guides
Guides to get you started with Statsig in no time
SDKs and APIs
Explore REST API and SDKs in more than 20 frameworks
Integrations
Learn more about connecting Statsig to your existing tools
A/B Testing Calculator
Looking for a place to start your A/B Test? Try out our calculator
How Statsig Works
Get under the hood and check out how Statsig scales with you
LEARN & CONNECT
Blog
Peak Velocity is our blog where we cover the latest in data
Support
Need help getting set up or have questions about our product?
Customer Stories
Find out how leading companies are using Statsig to grow
Events
Find out about our online and offline events and RSVP to them
Build vs Buy
Compare building an in-house platform vs. buying
Contact Sales
Want to connect with someone from the Sales team?
FEATURED BLOGS
Feature Flags Liberated
Gating features is a core part of the development process. And with Statsig, it's free.
How AI Companies Use Statsig
The best AI companies use Statsig to accelerate growth. Learn how you can do the same.
What is Product Observability?
Product observability means being able to monitor, control, and gain insight into all of your features.KEY FEATURES
GETTING STARTED
Documentation
Documentation to get you started with implementation
Walkthrough Guides
Guides to get you started with Statsig in no time
SDKs and APIs
Explore REST API and SDKs in more than 20 frameworks
Integrations
Learn more about connecting Statsig to your existing tools
A/B Testing Calculator
Looking for a place to start your A/B Test? Try out our calculator
How Statsig Works
Get under the hood and check out how Statsig scales with you
LEARN & CONNECT
Blog
Peak Velocity is our blog where we cover the latest in data
Support
Need help getting set up or have questions about our product?
Customer Stories
Find out how leading companies are using Statsig to grow
Events
Find out about our online and offline events and RSVP to them
Build vs Buy
Compare building an in-house platform vs. buying
Contact Sales
Want to connect with someone from the Sales team?
FEATURED BLOGS
Experiments with Generative AI
We built a generative AI app in reactJS using OpenAI’s API and Statsig. Here’s what we learned:
Experimentation Platforms
The decision to build versus buy an experimentation and feature flagging platform is not an easy one.
CUPED Explained
CUPED is an implementation that uses pre-experiment data to explain the variance in the result data.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 new, warehouse-native way to achieve statistical significance
In love with your flags and assignment tools? Add Statsig to your stack
for end-to-end experimentation including targeting and feature rollouts
with holdouts and layers
No extra overhead
Engineering teams can now liberally apply A/B testing on top of
feature flags, with zero overhead. Statsig Warehouse
Native provides a fast, responsive, and modular stats engine for
experimentation analysis directly in your data warehouse
Save time
Make updates to experiments and recover from mistakes in less than
20 minutes, instead of waiting 20+ hours for revised results using
other experimentation engines. Run experiment analyses in a matter
of minutes
Hybrid solutions supported
Use Statsig for experiment analysis, leverage SDKs for
end-to-end targeting and feature rollouts with holdouts and layers,
or import offline experiments as part of a hybrid solution. Statsig
meets you halfway, wherever that may be
