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Datalore VS Deepnote

Compare Datalore VS Deepnote and see what are their differences

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  3. » Reviews
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Datalore logo Datalore

Datalore is an interactive web-based workbook for data analysis, scientific exploration and visualization in Python.

Deepnote logo Deepnote

A collaboration platform for data scientists
  • Datalore Landing page
    Landing page //
    2022-12-17
  • Deepnote Landing page
    Landing page //
    2023-10-09

Datalore features and specs

  • Integrated Development Environment
    Datalore provides a sophisticated and user-friendly IDE specifically tailored for data science, offering features such as auto-completion, version control, and easy collaboration.
  • Collaboration Tools
    Allows multiple users to work simultaneously on the same notebook, enabling efficient teamwork with features like comments and real-time synchronization.
  • Built-in Libraries and Tools
    Includes pre-installed libraries essential for data analysis, machine learning, and visualization, which saves time compared to setting up environments from scratch.
  • Scalability
    Datalore can be connected to cloud computing resources, allowing users to scale their computations as needed, which is beneficial for handling large datasets.
  • JetBrains Ecosystem
    As a product of JetBrains, Datalore integrates well with other JetBrains tools and benefits from ongoing development and dedicated support.

Possible disadvantages of Datalore

  • Pricing Model
    While a free tier is available, advanced features and increased resource access require a paid subscription, which might be a barrier for some users.
  • Learning Curve
    Users not familiar with JetBrains' interfaces might find the transition to Datalore a bit challenging compared to more widely-used platforms like Jupyter.
  • Internet Dependency
    As a cloud-based service, a stable internet connection is necessary, which can be inconvenient or limiting in environments with poor connectivity.
  • Limited Offline Functionality
    Unlike local installations of Jupyter or RStudio, Datalore's functionality is limited offline, potentially restricting use cases where offline access is needed.
  • Resource Limitations on Free Tier
    The free tier has restrictions on computation time and resources, which may not be suitable for extensive or resource-intensive data analysis projects.

Deepnote features and specs

  • 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 of Deepnote

  • 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.

Datalore videos

+ Add

Star Trek: TNG Review - 1x13 Datalore | Reverse Angle

More videos:

  • Tutorial - Getting started with Datalore: online Jupyter notebook tutorial
  • Tutorial - Visualization Tutorial With Pyplot in Datalore by JetBrains

Deepnote videos

+ Add

Could this be the Best Data Science Notebook? (Deepnote)

Category Popularity

0-100% (relative to Datalore and Deepnote)

Datalore

Deepnote

Machine Learning
100 100%
Machine Learning
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Data Science Notebooks
100 100%
Data Science Notebooks
0% 0
AI
0 0%
AI
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Datalore and Deepnote

Datalore Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
One of JetBrains Datalore’s advantages is its interaction with the JetBrains ecosystem of tools, which includes IDEs like PyCharm and IntelliJ. That’s also why the tool is primarily aimed at ecosystem users.
Source: lakefs.io
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
JetBrains Datalore is a cloud-based data science platform that offers many of the same features as Jupyter Notebooks, as well as a number of additional capabilities. It supports a wide variety of programming languages, including Python, R, and SQL, and provides access to powerful hardware resources, including GPUs. One of the main advantages of JetBrains Datalore is its...
Source: noteable.io

Deepnote Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
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 well as include text, equations, and visualizations in a single document.
Source: lakefs.io
7 best Colab alternatives in 2023
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, Google Drive, and BigQuery. Its modern, intuitive interface makes it a compelling choice for both beginners and experienced data scientists.
Source: deepnote.com
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
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 programming languages, as well as include text, equations, and visualizations in a single document. Deepnote also has a built-in code editor and supports a wide range...
Source: noteable.io
The Best ML Notebooks And Infrastructure Tools For Data Scientists
A Jupyter-notebook enabled platform, Deepnote boasts of many advanced features. Deepnote supports real-time collaboration to discuss and debug the code. The platform will soon have functions such as versioning, code review, and reproducibility. Deepnote has intelligent features to quickly browse the code, find patterns in your data, and autocomplete code. It can integrate...
Source: analyticsindiamag.com

Social recommendations and mentions

Based on our record, Deepnote should be more popular than Datalore. It has been mentiond 34 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Datalore mentions (10)

  • Plotting Financial Data in Kotlin with Kandy
    For working with datasets (loading and processing), I use Kotlin DataFrame. It is a library designed for working with structured in-memory data, such as tabular or JSON. It offers convenient storage, manipulation, and data analysis with a convenient, typesafe, readable API. With features for data initialization and operations like filtering, sorting, and integration, Kotlin DataFrame is a powerful tool for data... - Source: dev.to / about 1 year ago
  • A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
    Datalore - Python notebooks by Jetbrains. Includes 10 GB of storage and 120 hours of runtime each month. - Source: dev.to / about 1 year ago
  • Best online course to actually learn to use Python
    Last 1/3 of course sections: More of the same really, thought I had sections where I had to install earlier iterations of Python due to incompatible libraries in some of the course sections. As ever, student comments & furious Stack Overflow searches were helpful. Also, Jupyter notebooks are introduced in this part of the course. As I'm using the Community Edition of Pycharm for the course AND the free versions... Source: about 2 years ago
  • A new take on a Jupyter interface
    - Do you know about https://datalore.jetbrains.com/? They seem to have this cool thing where you can rewind the state of the notebook using CRIU. I don't know how well this works in practice but I think it could help with experiment management, debugging and getting code to production. Source: over 2 years ago
  • New Jupyter Notebook competition
    Have you looked at Datalore, https://datalore.jetbrains.com/. Source: about 3 years ago
View more

Deepnote mentions (34)

View more

What are some alternatives?

When comparing Datalore and Deepnote, you can also consider the following products

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Saturn Cloud - 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.

Colaboratory - Free Jupyter notebook environment in the cloud.

Apache Zeppelin - A web-based notebook that enables interactive data analytics.

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.

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