-Great type-hinting and code completion you would expect from a JetBrains IDE.

-Great integration of external code repositories, with easy management of SSH keys. This has enabled us to accelerate our data processing by easy access to git managed tooling within Datalore.

-Reports and widgets generally within notebooks are great tools for creating simple scripts for a non-coder to execute to analyse data and produce results when desired. This has enabled us to free up data scientist resources for simple requests to reprocess similar data over and over.

-Cloud storage integration mounts storage onto the notebook making accessing data as simple as accessing local data is!

-Tech support is extremely quick to resolve a problem. Recently I opened a ticket about a specific install issue relating to a custom repo we had made. Within a couple days the tech support team had identified the issue with Datalore (conflicting Python versions) and rolled out a patch to fix the issue. Cannot beat the speed and effectiveness of their tech support - only praise!

-Billing is easy to keep track of, especially with itemised cost and storage usage that can be exported as a .csv for analysis (with a Datalore notebook itself).

-Database connection is as easy to setup as cloud storage. SQL cells are easy to use. We did find they ran quite slow, making them not useful for accessing larger databases and resulted to 'pandas' access manually. However I believe a patch sped these up, and I believe it was significant - though we have only utilised it in a limit capacity since the update.

-Notebook sheets and table of contents in particular, allow for easy organisation of notebooks via markdown headers that show on the ToC - making navigation of larger notebooks easy.

-Collaboration is great due to web-hosting of notebooks, allowing multiple users to edit a notebook simultaneously without any conflicts. Review collected by and hosted on G2.com.

-Python version is at 3.8 on notebooks. Have wanted to see a more modern version or options for a while, and despite plans to support multiple version from Datalore for over a year this hasn't happened.

-There are often issues accessing spot instances regularly for the CPU-XL tier forcing usage of on-demand or alternative computes, making spot CPU-XL almost unusable for us as an option.

-Minor gripe: markdown has spellchecking but cannot right click to fix the typo.

-On a wishlist: would like reports to be able to rerun a subsection of a notebook when called to (maybe a button widget), rather than having to rerun the entire notebook: this makes interactive reports unusable when having to load or process large data (since this is only needed once but reruns every small change). Review collected by and hosted on G2.com.

It's very flexible and transparent wrt pricing. The notebooks are reliable, and the overall look and feel is very intuitive and user friendly. Review collected by and hosted on G2.com.

Spot instances are rare, but I guess thats more of a problem of the backend orchestrator than Datalore itself. Nevertheless I'd expect more access to spot instances since the service in itself is not cheap. Review collected by and hosted on G2.com.

Easy to use , amazing data visulzation especial for beginners Review collected by and hosted on G2.com.

Nothing Ites frist platform I use I applyine frist Analysis for my data Review collected by and hosted on G2.com.

Interactive terminal with GPU and easy to create a report. Handy tool for complex Data Analysis tasks as well as coding. I like working on it. Review collected by and hosted on G2.com.

It should have Pylance support with multi-turn accessibility for vars reference as in VSCode. Review collected by and hosted on G2.com.

I have tried and worked on various platforms for my Data Science practice, Intern tasks, and other general tasks, but what I discovered recently became my absolute favorite i.e., Datalore platform. It is easy to use and implement. It provides Smart Coding Assistance(it offers intelligent code completion, suggestions, and refactoring tools for Python, R and other languages making coding smoother and less prone to errors). It is Jupyter Compatibility. It provides Powerful Visualization by creating interactive and informative plots and charts directly within the work environment. And lastly it has Real-Time Collaboration i.e., Work together with colleagues on notebooks and share results and analyses in real time. It is easy to integrate and I have used it frequently. Review collected by and hosted on G2.com.

There is nothing to dislike about Datalore platform. Review collected by and hosted on G2.com.

Datalore is the best online jupyter notebook I have used till date, it has got lots of features unlike its competitor Colab, datalore can execute SQL code within jupyter notebook, it has got a neat hierarchy and a great user interface, visualizations and data exploration are inbuilt as well. The files stay in the runtime and do not get refreshed often which is a great feature., Plus the enterprise edition has got analyticsSQL, analyticsPython analytics and scalable infrastructure data integrations which makes life easier! Review collected by and hosted on G2.com.

The machines provided in datalore are a bit slower to low and sometimes initialization takes longer than usual which is sometimes buggy, apart from this all the features are helpful! Review collected by and hosted on G2.com.