Notes, tasks, passwords, journal, files, calendar, contacts and bookmarks, with mood and medication tracking. Encrypted on your device. Open source, no ads, no trackers. Free forever; Pro is a one-time purchase.
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Which is more popular?
Based on our record, Logseq
should be more popular than Deepnote.
It has been mentioned 300 times since March 2021.
social mentions
300 vs 34
Note Taking popularity
100% vs 0%
alternatives listed
240+ vs 111
Base details
Website, pricing, platforms and company facts side by side.
Bidirectional Linking Logseq allows users to easily create bidirectional links between notes, enhancing organization and navigation through related information.
Graph View The graph view provides a visual representation of how notes are interconnected, helping users see the bigger picture of their knowledge network.
Markdown Support Logseq supports Markdown, making it easy to format notes and write in a widely-used plain text format.
Local Storage Notes are stored locally, giving users full control over their data and enhancing privacy and security.
Customizable Workflows Users can customize their workflows with plugins and templates to suit their specific needs and preferences.
Open Source Being an open-source project, Logseq invites community contributions and ensures more transparency in development and issue resolution.
Task Management Logseq integrates task management features, such as to-do lists and scheduling, directly within notes, improving productivity.
Possible disadvantages
Learning Curve New users may find Logseq's extensive features and unique workflow approach challenging to learn without dedicated time and effort.
Sync Complexity While storing notes locally is a pro for privacy, it requires additional tools or manual methods to sync notes across multiple devices.
Mobile App Limitations The mobile version of Logseq is still in development, meaning it may lack some features and fluidity found in the desktop version.
Resource Intensive Logseq can consume considerable system resources, particularly when dealing with large datasets or extensive use of graph view.
Community Dependency As an open-source project, certain features may rely on community contributions, which could lead to inconsistent updates or support.
Customization Complexity While high customization is a benefit, it can become overwhelming and complex to manage for users who prefer a more straightforward tool.
Collaborative Features Deepnote allows for real-time collaboration, similar to Google Docs, where multiple users can work on the same notebook simultaneously without conflicts.
Integration with Popular Tools Deepnote integrates seamlessly with popular data sources and tools such as Google Drive, GitHub, and SQL databases, enhancing its versatility for data science projects.
User-Friendly Interface The interface is clean and easy to navigate, making it accessible for both beginners and experienced data scientists.
Cloud-Based Being a cloud-based solution, Deepnote eliminates the need for local setup and maintenance, allowing users to access their projects from anywhere with internet access.
Data Security Deepnote provides robust security features, ensuring that your data and notebooks are protected against unauthorized access.
Integrated Version Control Version control within Deepnote allows users to track changes, revert to previous versions, and collaborate more effectively on shared projects.
Possible disadvantages
Limited Offline Access As a cloud-based platform, Deepnote requires an internet connection for most of its functionality, which can be a limitation for users needing offline access.
Performance Constraints Heavy computational tasks might be limited by the performance capabilities of the cloud resources provided, affecting users who require extensive computational power.
Subscription Costs While there is a free tier, advanced features and increased resource limits come at a subscription cost, which might be a consideration for students or hobbyists.
Learning Curve for Advanced Features While basic functionality is user-friendly, mastering the more advanced features and integrations may require a learning curve, especially for users new to data science tools.
Dependency on External Infrastructure The performance and availability of Deepnote can be affected by issues with their cloud service providers, which adds a layer of dependency on external infrastructure.
Analysis
An editorial look at what each product does well and who it suits.
LogseqDeepnote
Overall verdict
Yes, Logseq is generally considered a good tool, particularly for individuals seeking a robust, free-form method of organizing notes and knowledge that goes beyond traditional hierarchical models.
Why this product is good
Logseq is a versatile tool for managing notes and knowledge using a graph-based interface similar to networked thought processing. It offers features like linked references, back-linking, and support for Markdown and org-mode, making it a valuable tool for those who value interconnected note-taking. Its open-source nature ensures constant community-driven improvements and transparency, encouraging a strong user community.
Recommended for
Students and researchers who manage a large volume of interconnected notes.
Professionals who require a flexible and dynamic knowledge management system.
Writers and content creators looking for a tool to visualize ideas and concepts.
Tech enthusiasts and developers who appreciate open-source software.
Overall verdict
Deepnote is an excellent tool for data scientists, particularly those who value collaboration and need interactive, shareable notebooks. Its user-friendly interface and powerful integration capabilities make it a strong contender in the data science notebook space.
Why this product is good
Deepnote is a collaborative data science notebook designed to enhance productivity and simplify the data science workflow. It offers real-time collaboration, similar to Google Docs, making it easier for teams to work together efficiently. It supports various programming languages and integrates seamlessly with popular tools such as Jupyter notebooks, Git, and cloud storage services. Deepnote also provides a strong focus on data visualization and interactive dashboards, making it easier to interpret and present data insights.
Recommended for
Data scientists who work in teams and need a collaborative environment.
Professionals who require seamless integration with existing tools and cloud storage.
Users who prioritize interactive data visualization and interpretability.
Educators looking for an accessible platform to teach data science concepts.
Logseq is a powerful and advanced tool for thought that has been gaining attention among note-taking enthusiasts and productivity seekers. In this article, we will provide an overview of Logseq, explore what users can...
Outliners (think Workflowy, Roam, Logseq) rely on blocks and indentation for primary connections, and references to other blocks or pages for richer links. They’re optimized for capturing quick thinking.
Refined user interface: Logseq offers a refined user interface that is easy to understand and pleasing to the eyes. On the other hand, Obsidian looks like a jumble of various UI elements which are hard to figure out...
Deepnote is a cloud-based data science notebook platform comparable to Jupyter Notebooks but with a focus on real-time collaboration and editing. It lets users write and run code in several programming languages, as...
Deepnote is a real-time collaborative notebook. It offers features like real-time collaboration, version control, and smart autocomplete. It also provides direct integrations with popular data sources like GitHub,...
Deepnote is a cloud-based, data science notebook platform that is similar to Jupyter Notebooks, but with a focus on collaboration and real-time editing. It allows users to write and execute code in a variety of...
Using Logseq[1][2] for years and quite happy with it, especially since it has apps for tablets/iPad and phones as well, while being completely FOSS. [1] https://logseq.com/ [2] https://github.com/logseq/logseq.
- Source: Hacker News
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4 months ago
Choose a local Markdown tool like Obsidian, Logseq, Foam, or Tolaria to store all your knowledge as plain .md files you own and control.
- Source: dev.to
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6 months ago
Forgetful gets procedural and prospective memory
I should call out another thing that convinced me was a user of forgetful (twsta) posted in the discord a skill for managing wok and todos from how they used to use Logseq.
- Source: dev.to
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8 months ago
Thank you for the list - I think I've come across all of these in my research! I'll try highlight the differences for each. - https://noteable.io/ - as you say, it doesn't exist anymore - https://deepnote.com - I actually mentioned this...
- Source: Hacker News
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over 2 years ago
Deepnote - A new data science notebook. Jupyter is compatible with real-time collaboration and running in the cloud. The free tier includes unlimited personal projects, up to 750 hours of standard hardware, and teams with up to 3 editors.
- Source: dev.to
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almost 3 years ago
ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.
Joplin is a free, open source note taking and to-do application, which can handle a large number of notes organised into notebooks. The notes are searchable, tagged and modified either from the applications directly or from your own text editor.
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