Split and Eppo compared

Split and Eppo are both feature management and experimentation platforms that enable faster, safer feature releases.

While Split focuses on feature flags, testing, and observability, Eppo differentiates itself with a warehouse-native architecture that ensures metric governance, impact measurement, and data privacy for advanced A/B testing accessible to everyone in an organization.

What is Split?

Split is a feature management and experimentation platform that combines feature flags, testing, and observability to help product development teams release features faster and with less risk. The platform enables teams to ship updates more frequently while instantly detecting the impact of every feature they release.

Split's core offerings include:

• Feature flags: Deploy code when you want and release when you're ready

• Targeting rules: Gradually release features to segments of your user base

• Dynamic configuration: Manage complex releases with less stress

• Experimentation: Test in production and make data-informed decisions

Split's platform is designed for complex and highly regulated organizations in various industries such as financial services, healthcare, media, and software. It provides capabilities that ensure governance, flexibility, and automation of processes for teams that require these features.

The platform is architected for performance, security, and resilience. It uses a streaming architecture that pushes changes to its SDKs in milliseconds and evaluates feature flags locally to protect customer data.

What is Eppo?

Eppo is a next-generation experimentation platform designed for modern data teams. It offers an end-to-end solution that makes advanced A/B testing accessible to everyone in an organization, enabling businesses to accelerate experiment velocity without compromising rigor.

Eppo's core offerings include:

• Experimentation: Leverages a warehouse-native architecture to power a world-class statistical engine

• Feature Flagging: Provides fast and resilient feature flags for A/B tests, feature gates, and controlled rollouts

• Personalization: Unlocks new possibilities using Contextual Bandits, optimizing user experiences in real-time

• AI Model Evaluation: Allows businesses to build more effective AI products by evaluating models through experiments

Eppo's platform is geared toward fast-growing teams looking to unlock advanced experimentation methods such as holdouts, contextual bandits, and mutually exclusive experiments. It is designed for organizations seeking self-serve experimentation and expert guidance to build a culture of experimentation.

The platform integrates with popular tools such as Snowflake, Google BigQuery, Amazon Redshift, Databricks, LaunchDarkly, Optimizely, RudderStack, Segment, Split, DBT, and Google Analytics.

Pricing comparison

Split offers a free plan with basic features and 50,000 monthly tracked keys. Paid plans start at $35 per seat per month, with an Enterprise plan providing custom pricing and seats.

Eppo's pricing information is not publicly disclosed on their website. They offer customized pricing based on factors like usage volume, experiment complexity, and required support level.

Considerations and limitations: Split

Split is well-suited for complex organizations with strict governance and security requirements. The platform's advanced capabilities in feature delivery, control, and process automation make it an ideal choice for industries with high regulatory compliance needs, such as finance and healthcare. Split's architecture, designed for performance and resilience, also makes it a good fit for teams prioritizing these aspects in their feature management and experimentation practices.

However, Split may have some limitations for certain use cases. The platform's extensive feature set and advanced capabilities could introduce higher costs for smaller teams or startups with limited budgets. While Split offers powerful experimentation tools, there is limited information on their website about advanced techniques like contextual bandits, which may be a consideration for teams looking to implement more sophisticated experimentation strategies.

• TL;DR: Split is better suited for complex organizations with strict compliance requirements and teams prioritizing performance and resilience, but may have limitations for smaller teams or those seeking advanced experimentation techniques.

Considerations and limitations: Eppo

Eppo is well-suited for fast-growing teams seeking advanced experimentation methods like contextual bandits, personalization, and AI model evaluation. The platform's integration with popular data warehouses and analytics tools makes it an ideal choice for organizations with existing data infrastructure. Eppo's expert guidance and support can also be beneficial for teams looking to build a strong experimentation culture.

However, Eppo's lack of transparent pricing information on their website may be a limitation for some potential customers. Teams without existing data infrastructure may face challenges in adopting Eppo, as the platform relies heavily on integration with data warehouses and analytics tools. Additionally, there is limited information available on Eppo's collaboration and workflow features, which could be a consideration for teams with complex experimentation processes.

• TL;DR: Eppo is better suited for fast-growing teams with existing data infrastructure seeking advanced experimentation methods, but may not be the best fit for teams without established data practices or those requiring transparent pricing and extensive collaboration features.

An alternative: Statsig

Statsig is an all-in-one platform that offers experimentation, feature flags, and more. It's a great option for companies of all sizes, from startups to enterprises - trusted by Atlassian, Notion, and Microsoft. Sign up for a demo to see how Statsig can help you ship faster and drive growth.