Heptabase vs Tana: which should you choose in 2026?

Last updated May 2026

Heptabase and Tana are both tools for people who take knowledge management seriously. They share almost no design philosophy.

Heptabase is spatial. You think by placing cards on whiteboards, arranging them visually, and drawing connections you can see. The canvas is the thinking tool. Understanding emerges from arrangement.

Tana is structural. You think by tagging nodes with Supertags, defining fields, and writing queries that pull matching content dynamically. The database is the thinking tool. Understanding emerges from schema.

Same goal: making sense of complex information. Opposite methods. The choice is about how your brain works.

Side-by-side comparison

Where Heptabase wins

Visual thinking. If you understand ideas by seeing them in space, Heptabase is built for you. Place cards on a whiteboard. Move them around. Draw connections. Cluster related concepts. Zoom out and see the shape of your thinking. The spatial canvas isn't a feature. It's the product. Tana has no spatial canvas at all.

PDF annotation. Upload a PDF, highlight passages, pull highlights onto cards on a whiteboard. The reading-to-thinking pipeline is smooth. For researchers working through academic papers, this workflow is specifically designed for them. Tana treats PDFs as attachments.

Offline access. Heptabase is offline-first. Everything works without internet. Tana is cloud-only. If you work in libraries, on planes, or in low-connectivity environments, this is a practical advantage.

Mobile. Heptabase has functional iOS and Android apps. Tana's mobile app is capture-only. You can add nodes and voice memos but can't work with your graph, run queries, or do anything substantive on your phone.

Learning curve. Heptabase is more intuitive. The whiteboard model is natural: place things, arrange them, connect them. Most people are productive within a day or two. Tana's Supertag system takes weeks to understand and months to refine.

Collaboration. Real-time whiteboard collaboration, free for invited collaborators. Tana has shared workspaces but no spatial collaboration.

Where Tana wins

Structured data. Tana's Supertags are its core innovation. Tag a node as #meeting and it automatically gets fields for date, attendees, action items, and status. Tag it as #book and it gets author, rating, genre. Define the schema once, and every node of that type is structured consistently. This is a personal database that lives inside your notes. Heptabase has tags and tables within whiteboards, but it's not a database tool.

Dynamic queries. Live search nodes pull matching content from across your graph in real time. Want to see all #meetings with #client-x from the last month? Write a search node. It updates automatically as you add new content. Heptabase has search. Tana has programmable views.

Automation. Command nodes chain multiple AI operations together. Process a meeting transcript, extract action items, tag attendees, update a project status, all in one automated flow. Heptabase's AI explains and researches. Tana's AI takes actions.

Calendar integration. Google Calendar events sync into Tana as nodes with the appropriate Supertag. Your calendar becomes part of your knowledge graph. Heptabase has no calendar integration.

Free tier. Tana has a free plan (500 AI credits, 0.5GB). Heptabase has no free plan, only a 7-day trial.

Where both fall short

Both are text-first. Video, audio recordings, slide decks, spreadsheets, design files, emails. Neither tool extracts, indexes, or searches inside these content types. If your knowledge comes from more than text notes and PDFs, both leave gaps.

Both require significant investment. Heptabase asks you to arrange cards spatially over weeks and months. Tana asks you to design Supertag schemas, write queries, and maintain structures. Both reward effort. Both punish neglect. Neither system maintains itself.

Neither has semantic search. Heptabase has fast full-text search. Tana has powerful structured queries. Neither lets you search by meaning: "find everything I've saved about pricing strategy" in your own words, regardless of how you tagged or arranged it.

Neither handles diverse content. Meeting recordings, saved web articles with full extraction, images understood by AI, video searchable to the timestamp. Neither tool provides this.

Limited integrations. Heptabase connects to Readwise. Tana connects to Google Calendar. Neither has an API. Neither connects to Google Drive, Dropbox, Notion, or the broader ecosystem of tools where content already lives. Both ask you to bring everything inside manually.

AI is bounded. Heptabase's AI Tutor explains individual sources. Tana's AI processes individual nodes. Neither AI understands your entire library across all content types. Neither answers questions that span everything you've saved.

A third option: what if you didn't have to choose a paradigm?

Heptabase says: think visually. Tana says: think structurally. Both are valid. Both require you to commit to one way of representing knowledge and maintain that system indefinitely.

Fabric asks a different question: what if you didn't have to choose?

Fabric has a spatial canvas for visual thinking. Drag files, notes, PDFs, and links from your library onto an infinite space. Live embeds bring Figma designs, YouTube videos, Google Maps, and Slides into the canvas as working elements. The AI understands what's on the board. Real-time multiplayer.

Fabric also has structure. Spaces, folders, tags, kanban views, grid/list/detail modes. Organise as much or as little as you want.

But the core difference is that Fabric doesn't require either paradigm to work. The Memory Engine maps relationships between content automatically. Semantic search finds things by meaning, not by board position or Supertag query. The AI assistant understands your entire library across all content types, not just the notes you've written.

You don't arrange cards for weeks before the system reveals structure. You don't design schemas for months before queries return useful results. You save things. The AI handles the connections. You ask questions and get answers.

Heptabase rewards visual thinkers who maintain their whiteboards. Tana rewards system-builders who maintain their schemas. Fabric rewards everyone else.

See the full comparisons: Fabric vs Heptabase and Fabric vs Tana.

How to choose

Use Heptabase if you think spatially. You understand ideas by arranging them visually on whiteboards and drawing connections. You read PDFs and want a highlight-to-card workflow. You need offline access. You want collaboration on shared canvases. And you'll maintain your whiteboards consistently.

Use Tana if you think in systems. You want typed objects with structured fields and dynamic queries. You enjoy designing schemas and automating workflows with command nodes. You're comfortable with a steep learning curve. And you'll maintain your Supertag architecture over time.

Try Fabric if you want canvas when you need it, structure when you need it, and AI that understands everything in between. No paradigm to commit to. No system to maintain. All content types handled. Search by meaning. Generous free plan.

FAQs

Can I do spatial thinking in Tana?

No. Tana has no spatial canvas. All organisation happens through Supertags, links, and queries. If visual arrangement is part of how you think, Tana doesn't support it.

Can I do structured data in Heptabase?

Heptabase has tags and tables within whiteboards, but it's not a database tool. You can't define typed objects with structured fields, dynamic queries, or automated workflows the way Tana can.

Which is harder to learn?

Tana. The Supertag system, query syntax, and automation via command nodes take weeks to learn and months to refine. Heptabase's whiteboard model is more intuitive, though building a comprehensive knowledge graph still takes sustained effort.

Which has a better free tier?

Tana. Free plan with 500 AI credits and 0.5GB storage. Heptabase has no free plan, only a 7-day trial.

Do either of them have semantic search?

No. Heptabase has fast full-text search. Tana has structured queries. Neither searches by meaning. Fabric does.

What if I want both spatial thinking and structured data?

Neither tool offers both paradigms. Fabric has a spatial canvas with live embeds alongside structured organisation (Spaces, folders, tags, kanban, multiple views), and AI that understands your content regardless of how you've arranged it. Different approach to the same problem.

Which is better for PhD students?

Heptabase for building conceptual frameworks from academic papers through the PDF annotation and whiteboard workflow. Tana for systematically cataloguing papers, authors, and concepts with structured Supertags. Fabric for connecting everything across your entire research library with AI that understands all file types. See Fabric vs Heptabase and Fabric vs Tana for detailed comparisons, or see comparison of the best apps for PhD students.