Data as of Oct 7, 2026A topic in Product Analytics and Session Replay.
Reviewed by Dimitry Apollonsky
ChatGPT SearchSep 22, 2026
If by event modeling you mean defining events, properties, relationships, funnels, cohorts, and derived metrics without writing SQL, I’d shortlist these:
| Tool | No-SQL event modeling | Best fit | Key distinction |
|---|---|---|---|
| Amplitude | ⭐⭐⭐⭐⭐ | Product teams doing sophisticated behavioral analysis | Strong event/property segmentation, cohorts, derived metrics, governance |
Google AI ModeSep 18, 2026
I'm looking for a no-SQL solution for event modeling within a product analytics tool. What do you suggest?
| ⭐⭐⭐⭐⭐ |
| Fast self-serve product analytics |
| Very approachable funnels, retention, cohorts, and event-property analysis |
| PostHog | ⭐⭐⭐⭐½ | Developer-led teams | Analytics + replay + feature flags + experimentation in one platform |
| Heap | ⭐⭐⭐⭐⭐ | Minimal instrumentation | Autocaptures interactions so you can define/analyze events retrospectively |
| Pendo | ⭐⭐⭐⭐ | Product analytics + onboarding | Analytics tightly integrated with in-app guides/adoption |
For the richest no-SQL event modeling: Amplitude. Its Event Segmentation lets you combine events, event properties, user segments, filters, and group-bys without SQL, and it supports custom events and metrics.
For the simplest analyst/PM workflow: Mixpanel. It's particularly oriented around self-serve funnels, cohorts, retention, and segmentation rather than making you build queries yourself.
For "I don't want engineers constantly instrumenting everything": Heap. Its autocapture model lets you capture interactions first and define events from that captured data later.
For an engineering-heavy startup: PostHog is compelling because product analytics sits alongside session replay, feature flags, experimentation, and other product tooling.
One important distinction: no-SQL analysis isn't the same as no instrumentation. Even Amplitude's PM workflow assumes events are flowing into the project; engineers generally still need to instrument the underlying event stream.
If you tell me whether you're modeling B2B SaaS, consumer/mobile, or an AI product, I can narrow this to the 2–3 tools that fit your event model and show how I'd structure the events/properties in each.
When doing event-based product analytics and event modeling without writing SQL, you generally look for tools featuring visual query builders, codeless/autocapture capabilities , or behavioral data graphs.
Top platforms handling event modeling and analysis entirely through intuitive, no-code interfaces include:
If you want to narrow this down, tell me:
Yes. If your main requirement is “I want to define/model events and analyze them without writing SQL,” I’d shortlist these:
| Tool | No-SQL event modeling | Best fit |
|---|---|---|
| Mixpanel | ⭐⭐⭐⭐⭐ | Best pure product analytics experience |
| Amplitude | ⭐⭐⭐⭐⭐ | Best for sophisticated product teams |
| PostHog | ⭐⭐⭐⭐½ | Best all-in-one / engineering-friendly option |
| Heap | ⭐⭐⭐⭐½ | Best if you want automatic event capture |
Mixpanel is probably the closest match. Its core workflow is visual: select events, properties, filters, cohorts, funnels, and user flows rather than constructing SQL. Independent comparisons also consistently describe Mixpanel as particularly friendly to non-technical PMs.
A particularly interesting development is Mixpanel's 2026 data model: its Warehouse Connectors let you point-and-click at a Snowflake, BigQuery, or Databricks table and treat each row as an event, without building ETL scripts.
Amplitude — choose this if you need very deep behavioral analysis, sophisticated cohorts/retention, and a more enterprise-oriented product analytics platform. Amplitude explicitly positions its analytics around event-based modeling and offers a visual interface alongside more advanced capabilities.
PostHog — excellent if you want analytics + session replay + feature flags + experiments in one product. Its autocapture also means you can define events retroactively from captured behavior rather than having to anticipate every event beforehand.
Heap — worth considering if your priority is minimal instrumentation. It emphasizes autocapture, so you can capture behavior without manually defining every event upfront.
If you tell me what you mean by “model events”—e.g. define events from raw data, create derived events, join events together, change event definitions retroactively, or simply build funnels without SQL—I can narrow this to the 2–3 best tools for your exact workflow.
