Logseq vs Tana
Logseq is a free, open-source, local-first outliner with flashcards and a privacy-first ethos; Tana is an AI-native outliner where “supertags” turn notes into structured, queryable objects — two different takes on personal knowledge management. Here’s how they compare on pricing, platforms, linking, search, capture and collaboration — and how to decide between them.
What is Logseq?
Logseq is the open-source counterpart to Roam: an outliner built on bidirectional links and daily notes, but storing everything as local Markdown (or Org-mode) files on your device. It’s free, AGPL-licensed, and adds flashcards with spaced repetition, PDF annotation, queries, whiteboards and a plugin ecosystem. Sync is available end-to-end encrypted, or you can roll your own with Git or Syncthing.
The project is mid-transition: alongside the classic Markdown version, a rebuilt “DB version” backed by a local database entered public beta in July 2026, bringing real properties and Tana-style structured tags plus more reliable sync. That rewrite consumed several years of development attention, so the classic version evolved slowly — but the foundation of free, local, open-source outlining has kept a devoted community.
What is Tana?
Tana’s big idea is the supertag: slap #meeting or #person on any outline node and it gains fields, views and behavior — your notes become a queryable database without leaving the outline. Live queries collect matching nodes anywhere in your workspace, which makes Tana feel like Roam and Notion fused together.
Since 2025 Tana has pivoted hard into AI: a meeting agent that transcribes calls without a bot, voice capture that structures itself, semantic search, and a local MCP server so AI assistants can work with your workspace. In March 2026 the company split in two — the notes tool became Tana Outliner (outliner.tana.inc, the product compared here), while the plain “Tana” name moved to a separate agentic meeting platform. Outliner pricing as of September 2026: Free with 500 AI credits a month, Plus at $8/month and Pro at $14/month (22% off billed yearly; students, academics and NGOs get 50% off). It’s cloud-based with web, desktop and capture-focused mobile apps.
Logseq vs Tana at a glance
| Logseq | Tana | |
|---|---|---|
| Price | Free (open source); optional paid sync | Plus $8/mo; Pro $14/mo (22% off yearly) — Tana Outliner, Sep 2026 |
| Free plan | Yes — everything | Yes — 500 AI credits/mo, 3 workspaces, 0.5 GB |
| Platforms | Windows, macOS, Linux, iOS, Android | Web, macOS, Windows; iOS/Android capture apps |
| Storage model | Local-first — Markdown/Org files (DB version: local database) | Cloud |
| Editing model | Outliner — blocks, references, daily notes | Outliner with supertags (typed nodes, fields, live queries) |
| Backlinks & wiki links | Yes — bidirectional, block-level | Yes — references and backlinks |
| Graph view | Yes — graph view | No traditional graph view |
| Search | Full-text and queries | Full-text, structured queries, semantic AI search |
| Web capture | Community clippers; mobile quick capture | Mobile capture apps, voice capture |
| Email-in capture | No | No |
| RSS / feeds | No | No |
| Team collaboration | No | Yes — real-time shared workspaces |
| Publishing & sharing | Static-site export via community tools | Shared/published nodes |
| AI assistant access | Community plugins and MCP servers | Deep native AI (credit-metered) + local MCP server in the desktop app |
| Offline access | Yes — fully offline | Partial — desktop app, personal workspaces |
| Open source | Yes — AGPL-3.0 | No |
| End-to-end encryption | Yes — Logseq Sync is end-to-end encrypted | No |
| Data export | Markdown/Org files; OPML, JSON | Markdown or JSON workspace export (supertags flatten) |
Pricing and features as of mid-2026 — check each product’s site for current details.
New to personal knowledge management? Start here: choosing a second brain app — every tool on this page, with a pick for each kind of thinker.
Where Logseq shines
- Free and open source (AGPL) with local-first storage — the strongest ownership story among outliners.
- Built-in spaced-repetition flashcards and PDF annotation, no plugins needed.
- Block references, queries and whiteboards cover most of Roam’s power features.
- The new DB version adds structured properties and tags with trustworthy sync.
Worth knowing: No real-time collaboration — it’s a single-player tool. The MD-to-DB transition splits the product; some features (like whiteboards) are temporarily missing from the DB beta. Polish and mobile experience trail the paid competition, and web capture relies on community tooling.
Where Tana shines
- Supertags are the most elegant structure system in the category — schema, views and queries grow naturally out of plain outlining.
- The AI feature set is the deepest here: botless meeting transcription, voice capture, agents, and semantic search.
- A local MCP server inside the desktop app makes it one of the few tools built for AI-assistant workflows.
- Real-time multiplayer workspaces work well for teams.
Worth knowing: AI usage is credit-metered on every plan and the free tier is thin (500 AI credits, 3 workspaces, 0.5 GB); serious use means Plus at $8/month or Pro at $14/month. Cloud-only and proprietary: no local files, no end-to-end encryption; export is Markdown or JSON, and supertags and fields flatten on the way out. The structure-first approach has a real learning curve; casual note-takers may find it over-engineered.
Which should you choose?
Choose Logseq if:
- You want Roam-style outlining without the subscription, as open-source software.
- Local files and end-to-end-encrypted sync are non-negotiable.
- You want flashcards built into the same tool as your notes.
Choose Tana if:
- You want notes with fields, views and queries — a database that emerges from writing.
- Meeting transcription and voice capture are core to your workflow.
- You’ll actually use enough AI to justify the price.
A third option: Dexi
If what you actually want is one searchable place for notes, bookmarks, newsletters and RSS — with tags, @mentions and [[wiki links]] that organize themselves as you write, semantic search that finds ideas even when the words don’t match, and an MCP server so Claude and other AI assistants can work with your notes directly — take a look at Dexi. It’s free for up to 1,000 notes, with no app to install.
Frequently asked questions
What is the main difference between Logseq and Tana?
Logseq is a free, open-source, local-first outliner with flashcards and a privacy-first ethos, while Tana is an AI-native outliner where “supertags” turn notes into structured, queryable objects. In practice, Logseq is best for privacy-conscious outliner fans who want Roam’s ideas as free, open-source local files; Tana is best for structured-thinking power users who want their notes to behave like a database, with AI doing the heavy lifting.
Which is cheaper, Logseq or Tana?
Logseq: Free (open source); optional paid sync (free plan: yes — everything). Tana: Plus $8/mo; Pro $14/mo (22% off yearly) — Tana Outliner, Sep 2026 (free plan: yes — 500 ai credits/mo, 3 workspaces, 0.5 gb). Prices as of mid-2026 — check each product's site for current rates.
Is Logseq or Tana better for teams?
Logseq — team collaboration: no. Tana — team collaboration: yes — real-time shared workspaces. If neither fits, Dexi's Team plan ($10/member/month) offers per-note sharing with team-wide search.
Which is better for personal knowledge management, Logseq or Tana?
It depends on how you work rather than on feature count. Logseq is the stronger personal knowledge management tool for privacy-conscious outliner fans who want Roam’s ideas as free, open-source local files; Tana for structured-thinking power users who want their notes to behave like a database, with AI doing the heavy lifting. Start with whichever matches your habits — both let you export if you change your mind.
Can I switch between Logseq and Tana?
Both tools let you get your data out — Logseq exports via markdown/org files; opml, json, and Tana via markdown or json workspace export (supertags flatten). Markdown is the common ground for most migrations, though block references, properties and other tool-specific structure typically need manual cleanup after import.
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