Synap
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Synap vs Logseq

Open-source spirit. Structure built in.

Logseq is an open-source, local-first outliner with a passionate community and a commitment to user ownership. Synap shares those values. The difference: Synap structures your data into typed records, with views that make the same data useful in different contexts.

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Synap and Logseq, side by side

Synap compared with Logseq
TopicLogseqSynap
UnitBlocks in an outline — no typed entitiesTyped records with property schemas
OrganizingManual links, tags and queriesStructure applied on capture, proposed to you
ViewsOutline and graphTable, board, calendar, graph and more
StorageMarkdown files on your diskYour own PostgreSQL database
DevelopersPlugin APIFull API, SDK, and MCP

Structuring on capture is part of Pod + AI (€100/month). On the Pod plan (€20/month), the agent you connect does the structuring through Synap's tools. Either way, changes arrive as proposals you review.

Where Logseq is strong

  • Open source, local-first
  • Outliner with bi-directional links
  • Active plugin community

Where they differ

Outlines vs. records

Logseq's fundamental unit is the block — a bullet in an outline. Blocks link to each other, forming a graph of connected text. It works beautifully for journaling, but it doesn't scale to structured data. A task is a block with a checkbox; a contact is a block with a name. “Show me all tasks due this week” needs tags and queries you maintain.

Synap's fundamental unit is the record — a typed object with a profile, properties, and relationships. A task has a status, priority, and due date as first-class fields. A contact has an email and a company. Because the data is structured, views can render it meaningfully: tasks on a board by status, contacts in a table by company, events on a calendar.

Organization vs. manual linking

In Logseq, every connection is manual. You type [[Page Name]] to link, add #tags by hand, and write queries in a custom syntax. The result can be rich, but it takes continuous effort. Stop for a week and new information sits unlinked.

In Synap, linking is handled for you. Capture a research paper and it's recognized as an article, the author extracted, and linked to related records by topic. The graph grows even when you're not thinking about structure.

Local files vs. a database you own

Logseq stores everything as Markdown files on your disk. That is genuine ownership — open the files in any editor. The trade-off: Markdown can't represent structured data well. Properties live in frontmatter, relationships in wiki-links, with no referential integrity or query optimization.

Synap stores data in a dedicated PostgreSQL database. Same ownership — self-host it, export it with pg_dump — with the power of a real database: typed columns, foreign keys, full-text search, and vector embeddings for semantic search. Your data, in a format that scales.

Common questions

How is Synap different from Logseq?

Logseq is an open-source outliner that stores everything in local Markdown and EDN files — great for privacy and local control. Synap runs on a dedicated server you own (PostgreSQL for data, Markdown for notes) and adds classification on capture, typed records, and table, board and calendar views. Both put ownership first; Synap adds structure and queries on top.

Is Logseq or Synap better for a daily-note workflow?

Logseq's journal-first outlining is excellent for daily notes. Synap is capture-first: you put anything in and it gets classified, daily note or not. Synap doesn't force a journal structure, but supports it as one pattern among many.

Can I import my Logseq graph into Synap?

Export your Logseq graph as Markdown. An agent connected to your pod, such as Claude Code, can read those files and write them into Synap as typed records, with links and properties. Each write arrives as a proposal you review, so nothing lands in your pod unseen.

Is Synap open source like Logseq?

Synap's backend, the Data Pod, is public on GitHub and built on open-source infrastructure (PostgreSQL, Typesense, pgvector, MinIO). The self-hosted Docker Compose setup lets you run your own pod on any server.

Your knowledge, structured for you.

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