PostHog vs LogRocket: Analytics vs. Session Replay

The Short Answer

The Fundamental Difference

PostHog was built as a product analytics platform that happens to include session replay. It combines product analytics with the tools you'd normally bolt on separately: session replay (replacing Hotjar), feature flags (replacing LaunchDarkly), A/B testing (replacing Optimizely), surveys, error tracking, and a CDP. It's designed to be the single platform your product team uses for everything from shipping to measuring to debugging.

LogRocket was built as a session replay and debugging tool that happens to include basic analytics. Its core strength is replaying user sessions with full context: Redux/Vuex application state, console logs, network requests, performance metrics, and Galileo AI that proactively surfaces struggle patterns. It's designed for frontend engineers who need to understand what broke and why — not for product teams who need to measure conversion funnels.

Neither approach is wrong. The question is what question you're trying to answer.

How to Think About This Decision

The right choice depends on 4 dimensions of your team's needs.

Feature Comparison

Session Replay

PostHog captures web and mobile session replays with console logs, network monitoring, DOM explorer, AI-powered session summaries, and feature-flag-triggered recording (you can record only users who see a specific experiment variant). Its replays are tightly integrated with funnels, cohorts, and experiments — you can click on a funnel drop-off and immediately watch the sessions of users who dropped.

LogRocket captures web and mobile replays with Redux/Vuex state capture (showing exactly what the application state was at every moment), Galileo AI that proactively surfaces UX struggle patterns across thousands of sessions, and tighter error-replay correlation (click on an error, see the exact session replay where it occurred). For frontend debugging, LogRocket's replay is deeper.

Verdict: PostHog for replay integrated with analytics and experimentation. LogRocket for replay integrated with debugging and error diagnosis.

Analytics

PostHog has a full product analytics suite: funnels, retention analysis, cohort creation, path analysis, correlation analysis (automatically identifies which behaviors correlate with conversion), group analytics (track organizations, not just users), custom formulas, and a native SQL editor (HogQL). If you need to answer "why did activation drop 12% this week?" — PostHog gives you the tools to find out.

LogRocket has basic analytics: graphs, trends, funnels, cohorts, retention, and paths. But it lacks SQL access, correlation analysis, group analytics, and custom formulas. Its analytics are designed to complement session replay — "show me the sessions of users who dropped off at step 3" — not to replace a dedicated product analytics platform.

Verdict: PostHog for deep product analytics. LogRocket for basic analytics that support replay investigation.

Experimentation

PostHog has native feature flags and A/B testing/experiments with holdout groups, mutual exclusion groups, and statistical significance calculation. You can create a flag, target it to specific user segments, run an experiment, and measure the impact — all in the same platform.

LogRocket has no experimentation capabilities whatsoever. No feature flags, no A/B testing, no holdout groups. If you need to run experiments, you need a separate tool.

Verdict: PostHog, by a wide margin. If your team runs experiments, LogRocket leaves a gap you'll need to fill elsewhere.

Error Tracking

PostHog captures errors in real-time with grouping, stack traces, release tracking, and direct connections to session replays and funnels. You can see which errors are causing funnel drop-offs and watch the sessions of users who hit those errors.

LogRocket specializes in frontend JavaScript error tracking with full replay context. Its error-replay correlation is tighter — you click on an error and immediately see the exact session where it occurred, including Redux state and network requests at the moment of the error. For debugging workflows, LogRocket is more mature.

Verdict: LogRocket for deep frontend error debugging. PostHog for error tracking integrated with product analytics.

Data Ownership and Compliance

PostHog is open-source and can be self-hosted. It offers EU data hosting, HIPAA compliance, and raw data access via SQL. For healthcare, fintech, and regulated industries, these are genuine differentiators.

LogRocket is proprietary SaaS only. No self-hosting, no HIPAA compliance mentioned, no EU-specific hosting option. Standard compliance features for B2B SaaS.

Verdict: PostHog for data ownership and compliance. LogRocket for standard B2B SaaS use cases.

Pricing Comparison

Free Tier

PostHog's free tier is 5× more generous for session replay and includes features LogRocket doesn't offer at any price (feature flags, A/B testing). Over 90% of PostHog companies remain on the free tier.

Paid Pricing

PostHog scales on usage: ~$137/month for 5M web events and 50K session replays. Billing limits prevent surprise charges. $50K in startup credits available for qualifying companies.

LogRocket scales on session volume and seats: Team at $69/month, Professional at $295/month (adds AI struggle detection and full product analytics), Enterprise at custom pricing for self-hosting and custom volumes.

Verdict: PostHog is cheaper at scale and more generous at zero cost. LogRocket's paid tiers are predictable but less feature-rich for the price.

When to Pick PostHog

• You want one platform, not multiple. Analytics + replay + flags + experiments + surveys in one tool. If you're currently paying for Amplitude + Hotjar + LaunchDarkly + a survey tool, PostHog will likely be cheaper and better integrated.
• You run experiments. Native feature flags and A/B testing with holdout groups. LogRocket doesn't have any experimentation capabilities.
• You need SQL access. The HogQL editor lets analysts query raw data directly. LogRocket has no SQL.
• You care about data ownership. Open-source, self-hostable, EU data hosting, HIPAA compliance. These matter for regulated industries.
• You're early-stage. 1M free events/month means you can build your entire analytics foundation before paying anything — and working with a PostHog consulting specialist at this stage costs far less than re-instrumenting after the data debt has built up.
• You have an engineering-led team. PostHog's interface is optimized for technical teams who want to query, experiment, and debug in the same platform.

When to Pick LogRocket

• Your primary need is frontend debugging. If your biggest pain point is "we don't know what's breaking in production," LogRocket's replay + error tracking + Redux state capture is purpose-built for that workflow.
• You already have a product analytics platform. If you're using Amplitude or Mixpanel and just need a debugging companion, LogRocket fills that gap without overlapping with your existing analytics tool.
• You're a frontend engineering team. LogRocket is built for frontend engineers who need to understand production UX issues. PostHog is built for product teams who need to understand user behavior.
• You need Galileo AI for struggle detection. LogRocket's AI proactively surfaces UX patterns across thousands of sessions. PostHog has AI session summaries but not proactive pattern detection.

What Users Say (G2 Data)

According to G2 user reviews, both tools score identically on overall rating:

Both tools score equally on meeting requirements and overall satisfaction. LogRocket edges out slightly on ease of use and setup — consistent with its focused debugging positioning. PostHog leads on direction of product, reflecting its rapid expansion of features (AI, CDP, error tracking).

FAQ