Logseq OG vs the database version: which should you use?

Short version: if editable plain Markdown files are why you use Logseq, stay on OG. If faster queries, linked references at scale, and the new database features are the draw, test the DB beta on a copy of your graph. It now has an optional Markdown Mirror, but the files it writes aren’t the graph’s editable source of truth. If neither answer feels right, there’s a third door at the end of this post.

Logseq announced the product split on April 24, 2026: Logseq OG is the original file-based Markdown app, while Logseq is the database app. On July 13, the team released its first public DB beta. OG moved to maintenance mode; the database app is where new feature work goes.

What “maintenance mode” actually means

It means security fixes and patches, plus Electron and dependency upgrades. It doesn’t mean new features. Your Markdown files still work, your graph still opens, and there is no migration deadline.

That makes OG a sensible long-term choice if it already fits. The tradeoff is that fixes and new work for the database app won’t arrive there. A mature workflow can be worth more than a newer architecture.

The cost shows up gradually. Plugin authors and integrations will increasingly aim at the app under active development. OG serves the file-first workflow; the database app’s roadmap directs its future features.

What the database version changes

The headline change is storage. The database app keeps the graph in local SQLite, and that database is canonical. Logseq has now shipped a Markdown Mirror: opt in for a graph and the app writes a Markdown projection to disk as you edit.

That is useful. You can search the mirror with grep, put it under Git, back it up, or open it in another Markdown editor. Logseq also has a Markdown export. But a mirror or export is not a file-based graph: edits flow from the DB to the files, not back from the files to the DB. Two-way editing is still marked in progress on the public roadmap.

For plenty of Logseq users, that distinction decides it. “My notes are editable Markdown files in a folder I control” was never a feature bullet; it was the reason to choose a local-first outliner. The database app can give you a useful Markdown copy on disk, but it does not give you canonical plain files. If that property matters most, OG remains the right product.

What you get in exchange is real:

• Performance at scale. Queries and linked references are faster, and the roadmap lists testing with 50,000 pages and more than a million blocks.
• End-to-end encrypted sync. Your data encrypts locally with your password before it goes to the server, and decrypts on the other device.
• Real-time collaboration, built on the same new sync work.
• Active development. Every new feature from here lands in this version and only this version.

The beta’s remaining limits are uneven:

• Sync, RTC, and self-hosting are at different stages. Sync and real-time collaboration are still preview access for Open Collective backers and sponsors; Logseq Pro remains in progress on the roadmap. Self-hosted sync is marked done, and the release notes support custom sync-server URLs.
• Mobile is available through test channels. The DB app is on iOS TestFlight and Android’s latest nightly APK. Native mobile apps remain in progress, despite the mobile fixes already landing in release notes.
• Whiteboards and Zotero take different paths. Whiteboards are absent from the DB app and remain a roadmap to-do. The roadmap marks a DB-version Zotero plugin done, so Zotero is now a plugin workflow rather than a core feature.
• The CLI and MCP are shipped. The CLI is bundled with desktop releases and can query, back up, and operate a graph without the desktop UI. The roadmap also marks Logseq MCP done.
• Backups now have product support. Desktop database graphs have automatic backups, and the CLI shares the same backup path. An independent backup and a test import on a copy remain wise; the beta release asks users to protect important data before trying it.
• Import deserves a rehearsal. A duplicate graph is the place to test the Markdown import tool. A one-way mirror is not a migration path back to a file-based graph.

Picking

Here’s the decision, without hedging.

OG is the better choice if your graph is mature, your workflow is muscle memory, and editable plain files matter to you. A maintenance-mode tool that does the job is worth more than a beta that changes the property you rely on. Two-way Markdown editing, rather than the one-way mirror, is the meaningful milestone.

The database beta is the better choice if you’re on Logseq for the PKM machinery rather than the file format: backlinks, queries, a big graph, and its new sync and collaboration work. That’s what the new version is built to serve. A month on a copied graph gives you a low-risk comparison. Markdown Mirror can provide an on-disk copy, but editing it won’t change the graph.

Waiting makes sense if you want the DB version but not the beta. OG is still available and the import path will improve.

The decision is reversible. A trial on copied data will tell you more than a long research loop.

For outline-first users

Plenty of people came to Logseq for the outline itself: fast nesting, one tree, and the ability to capture a thought before deciding where it belongs. The queries and graph view may be features they admire more than use.

For those people, the OG-versus-DB choice is mostly about features outside their daily work. One path is maintenance mode; the other is a beta migration.

listlis is built for that group. One tree, keyboard-first, no version to choose. A node is a title plus an optional Markdown body, so a line stays scannable until it needs room. The loop runs entirely from the home row: o adds a sibling below, Tab nests it under the row above, Shift-Tab pulls it back out, ! makes a node a todo, c completes it. Completion carries the subtree and rolls up to the root, so a finished branch reads as finished. / searches every node by title and body. Reordering is cheap because sibling order is a fractional index between neighbors, which means reparenting a whole subtree writes one row instead of renumbering a list.

The thing that tends to land with Logseq people is the query replacement. listlis exposes your tree to AI assistants over MCP, so you ask for the slice you want in plain language: pull everything about a project, tell me what’s due, drop this into the right branch. No query syntax, no per-node AI credits metered against you, no chatbot bolted into the sidebar. Getting the right slice of your own thinking back out was what queries were for. This does that job with less machinery in the way.

What listlis doesn’t do is reproduce Logseq’s datalog query engine or its backlink graph. If those are genuinely how you work, stay in the Logseq family and pick OG or DB on the terms above. Fit matters more than a pitch.

Where to go from here

If you’ve decided to leave, the calm guide to leaving Logseq walks the options one at a time, including the ones that aren’t us. If you’re comparing outliners more broadly, the comparison hub maps where each tool draws its line, and Workflowy vs Logseq covers the same ground from the other direction.

And if the third door is the one you want, open a root at app.listlis.com and start typing. Bring an OPML or Markdown outline from the import panel, or start with an empty root. No template gallery, no version to pick.