Datalore Help

What's new

The page lists keys features and updates of currently implemented Datalore Enterprise releases.

Full description of the latest release is available on the Datalore Enterprise landing page.


Major release details

New features

  • New installation option: possible to install Datalore Enterprise using easy-to-set-up Docker-based configuration

  • Coding and execution:

    • Scheduled runs for notebooks

    • Parameterized SQL statements

    • Computation tab

  • Collaboration: Collaborative editing of attached files

  • Databases:

    • Limiting database schemas for introspection

    • MS SQL Server support


  • Meaningful names of files downloaded from interactive reports

  • Database passwords no longer exposed in Test Connection pod

  • Collaborators allowed to change machine type in shared notebooks

  • More cut-off timer options for background computation


Release updates

Minor version



  • Added instance and storage gift codes

  • Jedi disabled by default to speed up kernel completion

  • Improved kernel stability following non-critical code errors

  • Fixed opening of notebooks with erroneous syntax info

  • Fixed dropdown value update in interactive reports

  • Improved kernel stability when using interactive controls in Reactive mode


  • Improved overall performance, especially when working with big DataFrames and using Statistics tab or Variable viewer

  • Fixed analysis server


  • Restarting kernel when detecting out of memory status to ensure uninterrupted cell execution

  • Faster DataFrame rendering

  • Data output download allowed to unauthorized users


Fixed Spring Core RCE vulnerability

Major release details

New features

  • Statistics tab: used to provide in-depth information on DataFrames

  • Table viewer: editor component for reviewing and editing CSV and TSV files from Attached data

  • Visibility control: cell type for collapsing other cells in interactive reports

  • Сut-off timer for background computation: option for setting the machine to shut down after a specific period of inactivity

  • User activity logging: feature used to track cell execution by a specific user

  • Reactive mode in interactive reports: automatic recalculation following user interaction with the report


  • Enhanced reports:

    • Full width mode

    • Automatically hidden empty code cells

    • Checkbox control (for interactive reports only)

  • Variable viewer: providing information on notebook object sizes

  • Notebook structure: ability to use duplicated worksheets

  • Improved editor experience:

    • Viewport extended when scrolling past the notebook last cell

    • Better indication of cells queued for processing


Release updates

Minor version



  • Hub updated to 2021.1.14194

  • Database connection sharing options:

    Shared workspace

    • Editors can create and edit database connections, and attach them to the notebooks of the shared workspace.

    • Editors can create and execute SQL cells for any connected database.

    • Viewers can view database connection lists and respective database schemas.

    Home workspace notebook

    Editors can create and execute SQL cells for any connected database.


  • Hiding worksheet inputs and outputs

  • Improved matrix rendering for the R kernel

  • Latest Lets-Plot library version

  • Visualize tab:

    • Bigger charts, improved chart settings layout

    • One-click chart export to a chart cell

    • R kernel support


log4j-related security issue in Hub


  • Rendering of Pandas series with custom indexing

  • Reactive mode for Kotlin


log4j-related security issue

Major release details

New features

  • Database connection: interface for connecting to databases from the Home page and the editor

  • Native SQL cells: cell type used to retrieve data from connected databases without passing user's credentials to the environment

  • Interactive reports: feature for publishing notebooks as pages that collaborators can dynamically change using interactivity elements

  • Chart cells: cell type used to build customizable visualizations based on dataframes in your notebooks

  • Interactive controls: dropdown, slider, and text input elements to quickly customize output without manually changing the code

  • Cell visibility control: interface used to select what input and output to hide from viewers

  • More language support: R and Scala available as notebook languages

  • Reactive mode: top-down evaluation with automatic recalculation of cells below the modified one


  • Environment: customization via initialization scripts in the file

  • Expanded Python support: Python 3.6 and later versions available with respective code insight features for each

  • Visualize tab: more plot types added (point, bar, area, correlation)

  • More bucket types: Google Cloud Storage buckets attachable to notebooks

  • Last cell execution info: last execution time shown when hovering over a cell

  • Cell collapsing: ability to collapse specific cell inputs and outputs for better coding experience

Last modified: 08 June 2022