The best Eppo alternatives & competitors, compared
Contents
1. PostHog
- Founded: 2020
- Similar to: Statsig, Amplitude
- Typical users: Engineers and product teams
What is PostHog?
PostHog (that's us π) is an open-source platform combining feature flags, A/B testing, product analytics, session replay, and surveys into one product. This means it's not only an alternative to Eppo, but also tools like Amplitude and Hotjar.
Typical PostHog users are engineers and product managers at startups and mid-size companies, particularly B2B companies. Customers include AssemblyAI, Hasura, Vendasta, and Airbus.
Key features
π© Feature flags: Rollout features safely with local evaluation (for faster performance), JSON payloads, and instant rollbacks.
π§ͺ A/B tests: Experiment in your app with up to nine test variations and track impact on primary and secondary metrics. Auto-calculate test duration, sample size, and statistical significance.
π Product analytics: Custom trends, funnels, user paths, retention analysis, and segment user cohorts. Also, direct SQL querying for power users.
πΊ Session replays: View exactly how users are using your site. Includes event timelines, console logs, network activity, and 90-day data retention.
π¬ Surveys: Target surveys by event or person properties. Templates for net promoter score (NPS), product-market fit (PMF) surveys, and more.
How does PostHog compare to Eppo?
Both Eppo and PostHog support core feature flag and A/B testing components. The biggest difference is their approach to data warehouses:
Eppo is warehouse-native, meaning that it integrates with your existing data tools like Snowflake or Postgres.
PostHog is not warehouse-native, but instead aims to replace your existing data stack by combining product analytics, pipelines, and warehousing into one platform. This eliminates the need for stitching together integrations between third-party tools, and makes it easier for engineers to work with data.
Besides this, PostHog offers product analytics, session replays, and surveys, whereas Eppo does not. On the other hand, Eppo offers multi-armed bandit testing (called "contextual bandits" in Eppo) and CUPED analysis, whereas PostHog does not.
PostHog | Eppo | |
Self-serve Free to try, no mandatory sales calls | β | β |
Warehouse-native Integrate with your existing data tools like Snowflake or Postgres | β | β |
Feature flags Deploy features safely with targeting and percentage rollouts | β | β |
Local evaluation Use local, cached flag values to increase speed | β | β |
Scheduling Schedule flag updates and rollouts | β | β |
Payloads Flags with string, number, or JSON payloads | β | β |
A/B testing Run tests and see the impact of changes with custom goals and reports | β | β |
Multi-armed bandit Optimize tests automatically by allocating traffic to the best performing variant. | β | β |
Statistics engine How the results of an experiment are calculated | Bayesian | Bayesian, Frequentist |
AI/LLM support Compare models with experiments, view performance, cost, and latency | β | β |
Open source Audit code, contribute to roadmap, and build integrations | β | β |
Transparent pricing Get pricing immediately without talking to sales | β | β |
Why do companies use PostHog?
According to G2 reviews, companies use PostHog because:
It's many tools in one: PostHog can replace Eppo (feature flags and A/B testing), Amplitude (analytics), and Hotjar (feedback and surveys). This simplifies workflows and ensures all product data is in one place.
They need a complete picture of users: PostHog includes every tool necessary to understand users and build better products. This means creating funnels to track conversion, watching replays to see where users get stuck, testing solutions with A/B tests, and gathering feedback with user surveys.
It's easy to get started: Many users love how PostHog's event autocapture means they can go from implementing its tracking code to ingesting events in just a few minutes. Enabling session replay is equally straightforward, so you can instantly start seeing how people are navigating your app or website.
Bottom line
PostHog is an ideal Eppo alternative if you're looking for a powerful all-in-one tool that can also serve your A/B testing and feature flag needs. It also offers a dedicated EU-hosted cloud at no extra cost.
2. GrowthBook
- Founded: 2020
- Similar to: LaunchDarkly, Statsig
- Typical users: Engineers and data scientists
What is GrowthBook?
GrowthBook is a warehouse-native feature flag and experimentation platform. Its biggest selling point is integrating with the product and data tools you already use.
It's a popular choice for companies in strict regulatory environments because it's self-hostable and warehouse-native, but you can also use its hosted cloud version.
Key features
π© Feature flags: Robust feature-flagging capabilities with custom targeting and scheduling.
π§ Warehouse-native: Designed to integrate seamlessly with your existing data tools like Snowflake or Postgres.
π§ͺ A/B testing: Experimentation suite built on feature flags with a visual editor to optimize UI changes.
π Analysis: Use either Bayesian or Frequentist engines. Connect your existing data and do retroactive analysis.
π Integrations: Connects with data warehouses and analytics tools, but has limited integrations beyond that.
How does GrowthBook compare to Eppo?
GrowthBook is the most similar alternative to Eppo on this list. It matches almost all of Eppo's features, plus has the added bonus of being self-serve with transparent pricing.
PostHog | Eppo | |
Self-serve Free to try, no mandatory sales calls | β | β |
Warehouse-native Integrate with your existing data tools like Snowflake or Postgres | β | β |
Feature flags Deploy features safely with targeting and percentage rollouts | β | β |
Local evaluation Use local, cached flag values to increase speed | β | β |
Scheduling Schedule flag updates and rollouts | β | β |
Payloads Flags with string, number, or JSON payloads | β | β |
A/B testing Run tests and see the impact of changes with custom goals and reports | β | β |
Multi-armed bandit Optimize tests automatically by allocating traffic to the best performing variant. | β | β |
Statistics engine How the results of an experiment are calculated | Bayesian, Frequentist | Bayesian, Frequentist |
AI/LLM support Compare models with experiments, view performance, cost, and latency | β | β |
Open source Audit code, contribute to roadmap, and build integrations | β | β |
Transparent pricing Get pricing immediately without talking to sales | β | β |
Why do companies use GrowthBook?
According to G2, reviewers choose GrowthBook for the following.
Warehouse-native: GrowthBook's integrations with the warehouses people are already using is a standout feature. It enables them to extract and make use of existing data.
Visual editor: The visual A/B test editor and experiment preview enable non-technical users to make full use of GrowthBook.
Self-hostable: Reviewers like that they have full control over GrowthBook by running it on their own infrastructure. This means no limits to data.
Bottom line
Being open source, free, and self-hostable, GrowthBook makes for a good alternative to Eppo, especially for companies in tricky regulatory situations.
3. Statsig
- Founded: 2021
- Similar to: LaunchDarkly, PostHog
- Typical users: Engineering and DevOps teams
What is Statsig?
Statsig provides tools like feature flags, experimentation, and analytics to help companies build better products. Teams use Statsig to take the risk out of releases, experiment with new features, and monitor changes. It also includes a warehouse-native mode to connect directly and utilize your data warehouse.
Key features
π© Feature flags: Take the risk out of releases with targeted feature flag rollouts.
π§ͺ Experimentation: Measure the impact of new changes with frequentist and Bayesian analysis engines.
π§ Warehouse-native: Designed to integrate seamlessly with your existing data tools like Snowflake or Postgres.
π Analytics: Provides a single location for your metrics. Enables users to dive deeper into them with trends, bar charts, and retention analysis.
How does Statsig compare to Eppo?
Statsig is another similar alternative to Eppo. It includes feature flags, warehouse-native mode, and advanced A/B testing techniques such as multi-armed bandit testing. However, its feature flags are limited to booleans only and don't support string, number, or JSON values.
Statsig | Eppo | |
Self-serve Free to try, no mandatory sales calls | β | β |
Warehouse-native Integrate with your existing data tools like Snowflake or Postgres | β | β |
Feature flags Deploy features safely with targeting and percentage rollouts | β | β |
Local evaluation Use local, cached flag values to increase speed | β | β |
Scheduling Schedule flag updates and rollouts | β | β |
Payloads Flags with string, number, or JSON payloads | β | β |
A/B testing Run tests and see the impact of changes with custom goals and reports | β | β |
Multi-armed bandit Optimize tests automatically by allocating traffic to the best performing variant. | β | β |
Statistics engine How the results of an experiment are calculated | Bayesian, Frequentist | Bayesian, Frequentist |
AI/LLM support Compare models with experiments, view performance, cost, and latency | β | β |
Open source Audit code, contribute to roadmap, and build integrations | β | β |
Transparent pricing Get pricing immediately without talking to sales |