Heap vs Hex: Which Is Better in 2026?

Heap is a product analytics platform distinguished by its autocapture approach, which automatically records every user interaction on your website or app without requiring you to manually define and track each event in advance. Traditional analytics force teams to decide upfront what to measure and write code for each event, which means you can only analyse what you thought to track — and you're stuck if you later want to study something you didn't anticipate. Heap solves this by capturing everything automatically, so the data is always there when a new question arises.

This autocapture foundation gives teams remarkable flexibility. Because every click, page view, and interaction is recorded, analysts and product managers can explore user behaviour retroactively, defining and analysing events after the fact rather than predicting their needs months earlier. On top of this complete dataset, Heap provides the analytics teams expect — funnels, retention, user paths, and segmentation — plus features that help surface insights and identify opportunities and friction in the user experience. The result is faster, more complete answers to questions about how people actually use a product.

Heap is used by product, growth, and data teams that want thorough behavioural insight without the limitations and ongoing engineering effort of manual event tracking. The value is completeness and agility: because the data is captured automatically and comprehensively, teams can answer new questions immediately instead of instrumenting tracking and waiting weeks to collect data. This is especially valuable for fast-moving teams that constantly explore new hypotheses about user behaviour. For organisations that want to deeply understand their users and iterate quickly on their products without being constrained by what they remembered to track, Heap's autocapture approach offers a powerful and flexible foundation for product analytics.

Hex is a modern, collaborative data workspace that brings together notebooks, SQL, Python and interactive data apps in one platform — designed to help data teams explore data, build analyses, and share insights far more effectively than traditional notebooks or BI tools allow. It blends the flexibility of a code notebook with the polish and shareability of a business intelligence tool, addressing the long-standing gap between how data scientists work and how the rest of the organization consumes their work.

In Hex, analysts and data scientists work in a flexible environment where they can mix SQL queries and Python code, connect to their data warehouses and sources, and build analyses fluidly. But the real magic is what happens next: with little extra effort, that exploratory work can be turned into a polished, interactive data app or report — complete with visualizations, filters and narrative — that stakeholders can use and explore themselves, without touching code. This collapses the usual gap between analysis and a shareable, presentable deliverable.

Collaboration and AI are central to the experience. Multiple people can work together in a project in real time, comment and build on each other's work, and Hex's AI features help write queries, explain code, and accelerate analysis. This makes data work more accessible and reproducible, and helps spread data literacy across teams. Hex is popular with data teams at modern companies who want to move beyond static dashboards and disconnected notebooks toward an integrated, collaborative analytics workflow. For organizations that want their data teams to explore, analyze and share insights in one powerful, collaborative and increasingly AI-assisted environment — and to turn analyses into interactive tools the whole business can use — Hex offers a compelling, contemporary platform.