PostHog vs Datibase: Which One Does Your SaaS Actually Need?
They both call themselves analytics. They're solving different problems.
PostHog and Datibase end up on the same shortlist surprisingly often. Both ship cookie-free defaults, both target indie founders and small teams, both have generous free tiers. From a feature comparison spreadsheet they look like two answers to the same question.
They aren't. PostHog is a product analytics suite — built around tracking what users do inside your app, with cohorts, funnels, session replay, and feature flags. Datibase is focused web analytics — built around tracking which traffic sources became paying customers. The overlap is the word "analytics"; the actual jobs are different.
We make Datibase, so we lean toward the "web analytics is enough for most SaaS" argument. PostHog has real strengths we'll call out honestly first.
What PostHog is genuinely great at
PostHog's core competence is in-app behaviour. If your product has users who spend hours inside it — a dashboard, an editor, a collaboration tool — you eventually need to answer questions like:
- Funnel drop-off inside the app: Where in onboarding do users abandon? Of the 100 who created an account, how many made it past step 3?
- Session replay: What did the user actually click on before they rage-quit? PostHog records sessions you can replay.
- Feature flags and experimentation: Roll out a feature to 10% of users, measure impact on retention, kill the flag if it tanks. Built in.
- Cohort retention curves: Of users who signed up in March, how many are still active in May? PostHog draws the curve out of the box.
- Self-host option: PostHog can be deployed on your own infrastructure if data sovereignty is a hard requirement.
For a product team running A/B tests inside a complex app, this is the right tier of tooling. Datibase doesn't do any of this and isn't trying to.
Where PostHog is heavier than most teams need
The price of generality is complexity. PostHog's SDK, dashboard, and pricing model are all calibrated for teams that will use the full suite. For a SaaS landing page plus a simple checkout flow, you end up with:
- A bigger script: PostHog's web SDK is meaningfully larger than the cookie-free options. Negligible if you already have heavy JS, painful on a marketing site optimised for LCP.
- Identification flow that wants consent: PostHog identifies users by default and stores identifiers — defensible legally with the right config, but most teams end up showing a banner anyway. The cookie-free defaults of Plausible / Fathom / Datibase don't have this problem.
- A dashboard built for explorers: PostHog rewards investment. The killer feature is being able to write SQL-style queries against events. If you don't, you'll only use 10% of the product and pay for 100%.
- Pricing tied to event volume, not value: Every page view, click, and feature flag check counts as an event. Volume can blow past the free tier faster than you'd expect on a successful launch day.
- No native payment integration: Revenue tracking exists via 'revenue events' that you fire from your backend. Functional, but it's still you wiring up Stripe webhooks — the same plumbing problem we wrote about in our Stripe revenue guide.
Where Datibase fits
Datibase answers a narrower question: which referrer source drove paying customers, this week? The full feature surface is sized to that question, not bigger.
That means: cookie-free script under 5 KB, no consent banner by default, a dashboard you can read in 30 seconds, and native Stripe / Polar integration so revenue shows up next to traffic without webhook plumbing. There is no session replay, no feature flags, no SQL editor. If those are dealbreakers, you want PostHog.
Side-by-side
| PostHog | Datibase | |
|---|---|---|
| Primary use case | Product analytics | Web + revenue |
| Cookie-free default | No (configurable) | Yes |
| Setup time | 30–60 min | 5 min |
| Script size | ~50 KB+ | Under 5 KB |
| Session replay | Yes | No |
| Feature flags | Yes | No |
| Funnels & cohorts | Yes | No |
| Native revenue (Stripe/Polar) | No (webhook DIY) | Yes |
| Self-host | Yes | No |
| Best for | Product teams | Indie SaaS founders |
How to actually pick
Two simple questions resolve the choice for most teams.
Do users spend significant time inside your app?
If yes — a dashboard, editor, BI tool, design tool — you'll eventually want session replay, funnels, and feature flags. PostHog. If your product is mostly a marketing site plus a checkout that hands off to a workflow, web analytics is enough. Datibase.
Is the next decision a marketing decision or a product decision?
Marketing decisions ('which channel should we double down on?', 'is this campaign working?') are answered by web analytics with revenue attribution. Product decisions ('which onboarding step is broken?', 'which feature drives retention?') need PostHog-class tooling.
The honest summary
Don't pick PostHog because it has more features. Don't pick Datibase because it has fewer. Pick the tool whose primary question matches the question you're actually trying to answer right now.
For most indie SaaS at the "a few hundred to a few thousand paying customers" stage, the urgent question is "which marketing channel pays back?" — and the answer requires revenue attribution, not session replay. If that's where you are, see also our broader Google Analytics alternatives review for context on the full field.
Connect traffic to revenue without webhook plumbing
Datibase ships native Stripe and Polar integrations — the revenue attribution that PostHog needs you to wire up yourself.
Try Datibase free