GrowthBook vs PostHog
An independent, review-free comparison compiled by the SaaSTracker editorial team. Both products are profiled in full, and neither can pay for placement here.
The short answer
Editorial assessmentGrowthBook compared with PostHog
PostHog gives you analytics, replay, flags, and experiments on one usage-based bill, which is unbeatable for convenience. GrowthBook does not collect your data at all and computes against your warehouse with a more configurable statistics engine. Take PostHog if you want everything in one place and no warehouse; take GrowthBook if you already have a warehouse and want experiment results you can audit line by line.
Choose GrowthBook if
Product and growth teams at small software companies who already have event data in a warehouse and want to run experiments with defensible statistics, plus engineering teams who want feature flags and the measurement of those flags in the same system without shipping user data to a vendor.
Choose PostHog if
Engineering-led SaaS and product teams that want web analytics, product analytics, replay, flags, and experimentation consolidated in one usage-priced platform, and that are comfortable doing their own revenue-attribution modeling if they need it.
Side by side
13 attributes| Attribute | GrowthBook | PostHog |
|---|---|---|
| Category | Product Analytics | Analytics |
| Starting price | $0 (Starter, 3 seats), then $40 per seat per month (Pro) (free plan available) | $0 (generous monthly free tiers; pay only past the allowance) (free plan available) |
| Pricing model | Per-seat subscription on cloud with a free tier, plus a free unlimited-user open source self-hosted edition and quoted Enterprise plans on both. Usage charges apply only to CDN delivery and the optional Managed Warehouse. | Usage-based pricing per product: every product has a monthly free allowance, then per-unit billing (per event, recording, flag request, survey response, or row) with steep volume discounts; optional platform packages add support and compliance features. |
| Free plan | Starter is free for up to 3 users and 1 project, with unlimited feature flags, unlimited experiments, and unlimited traffic. No credit card required. | 1M analytics events, 5K session recordings, 1M feature-flag requests, 100K exceptions, 1,500 survey responses, and 1M data warehouse rows per month, on 1 project with 1-year retention. |
| Free trial | No fixed trial; the free Starter tier and the open source build serve as the evaluation path | Not applicable; the free tier is permanent, not a trial |
| Best for | Product and growth teams at small software companies who already have event data in a warehouse and want to run experiments with defensible statistics, plus engineering teams who want feature flags and the measurement of those flags in the same system without shipping user data to a vendor. | Engineering-led SaaS and product teams that want web analytics, product analytics, replay, flags, and experimentation consolidated in one usage-priced platform, and that are comfortable doing their own revenue-attribution modeling if they need it. |
| Setup time | A day for a first experiment if you already have clean event data in a warehouse. Connect the data source, define two or three metrics, install the SDK, and launch. Without a warehouse, add however long it takes to get events landing somewhere, or use the Managed Warehouse to shortcut it. | Minutes to first data with the JS snippet and autocapture; days to weeks to define clean custom events, dashboards, and cohorts; warehouse sources and pipelines are a separate project. |
| Learning curve | Moderate and front-loaded on metric definition. The flag half is easy; the experimentation half asks you to think about conversion windows, denominators, guardrails, and priors. Teams that skip this get results that look precise and are not. The visible SQL helps, because a data-literate person can check the definition rather than trusting a label. | Low for the web analytics dashboard; moderate for funnels, cohorts, and replay; high for SQL insights, warehouse modeling, and experimentation statistics. |
| Platforms | JavaScript and React, Node, Python, PHP, Ruby, Go, Java, C# and .NET, Elixir, Kotlin and Android, Swift and iOS, React Native and Flutter, Cloudflare Workers, Fastly, and Lambda@Edge | Web app, JavaScript snippet and web SDK, Server SDKs (Python, Node, Go, PHP, Ruby, and others), Mobile SDKs (iOS, Android, React Native, Flutter), Self-hosted Hobby build (Docker, open source) |
| Compliance | GDPR posture strengthened by design: only aggregated statistics leave your infrastructure and GrowthBook collects no user data, Self-hosted deployment available behind a firewall for buyers who cannot use a processor at all, Confirm current SOC 2 scope with the vendor during procurement | SOC 2 Type II, GDPR, HIPAA (BAA on Boost, Scale, or Enterprise package) |
| Founded | 2020 | 2020 |
| Headquarters | Anaheim, California, United States | Remote-first; US-incorporated (San Francisco), team distributed globally |
| Ownership | Venture-backed, Y Combinator W22 | Venture-backed |
Strengths and limitations
GrowthBook
Strengths
- The statistics engine is genuinely serious: Bayesian by default with configurable priors, a frequentist option with sequential testing, CUPED variance reduction on both, and multiple testing corrections on dimensional breakdowns.
- Every result shows its SQL and exports to a Jupyter notebook, and the engine source is public, which makes results auditable rather than a vendor assertion.
- Warehouse-native architecture means your event data never leaves your infrastructure and only aggregate statistics reach GrowthBook, which shortens the data protection review considerably.
- Six automatic data quality checks including sample ratio mismatch catch the broken experiments that quietly poison decision-making elsewhere.
Limitations
- Per-seat pricing at $40 punishes larger teams; a fifteen-person product organisation on Pro pays $600 a month for capabilities that a smaller team gets for $120.
- You need a data source. Without a warehouse or the paid Managed Warehouse, GrowthBook has nothing to compute against, so it is not a first analytics purchase.
- Metric definition is real work in SQL, and the quality of every result depends on getting conversion windows, denominators, and capping right. There is no autocapture shortcut.
- Project limits are tight: one project on Starter and self-hosted open source, three on Pro, unlimited only on Enterprise.
PostHog
Strengths
- Breadth with real integration: analytics, replay, flags, experiments, surveys, error tracking, and a warehouse genuinely share one event stream and identity graph rather than being bolted-on acquisitions.
- The most generous free tier in the category, 1M events and 5K recordings monthly, permanently, which makes evaluation and early-stage use genuinely free.
- Open-source codebase plus a choice of US or EU (Frankfurt) cloud gives privacy and procurement teams inspectability and residency options most rivals lack.
- Usage pricing with automatic volume discounts and per-product spending caps scales from hobby project to hundreds of millions of events without a sales call.
Limitations
- No packaged B2B revenue attribution: connecting spend and touchpoints to CRM pipeline and closed-won revenue is a data-warehouse project in PostHog, not a built-in report as in Dreamdata or HockeyStack.
- Depth demands technical investment; non-technical marketers can read the web dashboard but will struggle to self-serve funnels, SQL insights, or warehouse joins.
- Usage-based billing is unpredictable without configured limits, and replay-heavy or autocapture-noisy sites can generate surprising invoices.
- The full event platform carries more GDPR surface than minimalist tools: consent, masking, and retention need deliberate configuration, where Plausible or Fathom are compliant nearly by default.
Pricing compared
GrowthBook
Per-seat subscription on cloud with a free tier, plus a free unlimited-user open source self-hosted edition and quoted Enterprise plans on both. Usage charges apply only to CDN delivery and the optional Managed Warehouse.
- Starter (Cloud)$0
- Pro (Cloud)$40
- Enterprise (Cloud)Custom
- Open source (Self-hosted)$0
- Enterprise (Self-hosted)Custom
Judged on statistics per dollar, GrowthBook is the best value in this category by a wide margin: sequential testing, CUPED, proper Bayesian inference with configurable priors, multiple testing corrections, and six automatic data quality checks are all present on a free tier. Judged on total bill, it depends entirely on headcount. Because the meter is seats rather than events, traffic volume barely matters: a product with 10,000 monthly users and one with 100,000 monthly users both cost the same, which is either a bargain or an irrelevance depending on your shape. A five-person team on Pro pays $200 a month; a twenty-person team pays $800, which is where the free self-hosted build with unlimited users starts to look attractive if you have the operational capacity. Against Statsig, whose free tier is enormous and whose statistics are comparably sophisticated, GrowthBook wins on warehouse-native architecture and auditability and loses on out-of-the-box analytics. Against Flagsmith or Unleash it costs more and does far more.
PostHog
Usage-based pricing per product: every product has a monthly free allowance, then per-unit billing (per event, recording, flag request, survey response, or row) with steep volume discounts; optional platform packages add support and compliance features.
- Free (no card)$0
- Pay-as-you-goUsage-based
- Platform packages (Boost, Scale, Enterprise)Quoted / package pricing
At small and mid scale PostHog is close to unbeatable on price: the permanent free tiers cover a real startup's entire measurement stack, and the per-unit rates undercut buying analytics, replay, flags, and experimentation separately. The honest caveat is that usage pricing shifts the budgeting burden onto you: a replay-heavy or event-noisy implementation can quietly cost more than a flat-rate point tool, and the platform packages needed for enterprise compliance are quoted, not listed. Treat it as extremely cheap by default and only as cheap as your instrumentation discipline at scale.
Editorial verdict on each
GrowthBook
InnovationGrowthBook is the experimentation platform to buy if you care whether the numbers are right. Sequential testing, CUPED, configurable Bayesian priors, multiple testing corrections, and automatic sample ratio mismatch detection are present on a free tier, and every result shows the SQL that produced it. That combination does not exist anywhere else at this price. The architecture is the other half of the argument: your data stays in your warehouse, only aggregates leave, and a self-hosted build with unlimited users is always available as an exit. Buy it if you already have event data in a warehouse and a habit, or an ambition, of running real experiments. Do not buy it as a first analytics tool, because it computes against data it does not collect, and do not assume the seat meter is cheap without multiplying $40 by your actual headcount. The work that determines your return is metric definition, and no vendor can do that part for you.
Read the full GrowthBook profilePostHog
Category LeaderPostHog is the default recommendation in this category for any team with an engineer on it: no rival matches the combination of a free-forever tier that covers real workloads, usage pricing that scales without a sales call, and genuinely integrated replay, flags, and experimentation on top of web and product analytics. The two honest reservations are that marketing teams without technical support will use a fraction of it, and that B2B pipeline attribution, the question GTM leaders most want answered, remains a do-it-yourself exercise on PostHog's warehouse rather than a shipped feature. Buy it as the behavioral system of record; budget separately if you need turnkey revenue attribution.
Read the full PostHog profileGrowthBook profile last reviewed 2026-08-22; PostHog last reviewed 2026-08-22. Pricing is compiled from public sources and can change without notice. See our methodology.