OpenHistory vs Logseq: Which is Better in 2026?
We've compared 2 tools across pricing, features, ratings, and reviews to help you make an informed decision. No paid placements — just facts.
Compare different tools →| Feature | OpenHistory Productivity & Automation |  Logseq Productivity & Automation |
|---|---|---|
| Rating | No reviews yet | No reviews yet |
| Pricing | Free as of Sep 30, 2026 |
as of Sep 18, 2026 |
| Pricing Model | Free | Freemium |
| Free Plan | ||
| Free Trial | ||
| API Available | ||
| Verified | ||
| Founded | — | — |
| HQ | — | — |
| Team Size | 1-10 | — |
| Platforms | — | — |
| Top Integrations | — | GitGitHubiCloudDropbox+1 more |
| Key Features |
|
|
| Description | OpenHistory is an open-source macOS app that builds a private, searchable timeline of a user's work by observing only the foreground activity they explicitly permit — window names, document context, browser domains, clicks, and visible interface text via macOS Accessibility APIs. It generates hourly and daily summaries and gives approved local AI agents a controlled way to answer questions about what the user did, using Apple's local Foundation Model by default or, optionally, OpenAI, Anthropic, or Kimi. By design, it does not capture screenshots, audio, camera or microphone input, passwords, private browser windows, or low-level keystrokes, and sends no analytics or telemetry of its own. All activity, timelines, summaries, settings, and agent connections are stored in a permission-restricted directory on the user's own Mac. It requires macOS 14 or later and is available on GitHub and via a direct download from its own site. | Logseq is a free, open-source (AGPL) note-taking and personal knowledge management app built around an outliner and a bidirectional-linked knowledge graph, storing everything as local Markdown/plain-text files. It's aimed at researchers, students, developers, and privacy-conscious individuals who want full control and ownership of their data rather than a cloud-locked notebook. What most sets it apart is its local-first, plain-text foundation combined with a powerful query language and an extensible plugin ecosystem. |