Release notes¶
- DSS 6.0 Release notes
- Migration notes
- Version 6.0.2 - December 5th, 2019
- Version 6.0.1 - November 6th, 2019
- Version 6.0.0 - October, 24th, 2019
- New features
- Managed Kubernetes clusters
- Managed Spark on Kubernetes
- Partitioned models
- Time series visualization
- New plugins experience
- Support for AWS Athena and Glue metastore
- SQL pipelines
- Global search toolbar
- Pluggable algorithms
- Pluggable webapps
- Pluggable chart types
- Pluggable custom view for folders and models
- Time series preparation
- Native Python processor in preparation
- Scenario reporting to Microsoft Teams
- Other notable enhancements
- Improved project folders
- Time-aware cross-validation and evaluation
- Enhanced Snowflake integration
- ADLS gen2 support in Azure dataset
- Python 3 support for base env
- New field types for plugins
- Redesigned contextual right panel
- Support for HANA Calculation views
- Managed standalone Hadoop libraries
- More native support for Amazon ECR
- Other enhancements and fixes
- New features
- DSS 5.1 Release notes
- Migration notes
- Version 5.1.7 - October 30th, 2019
- Version 5.1.6 - September 16th, 2019
- Version 5.1.5 - July 4th, 2019
- Version 5.1.4 - June 3rd, 2019
- Version 5.1.3 - April 11th, 2019
- Version 5.1.2 - March 1st, 2019
- Version 5.1.1 - February 13th, 2019
- Version 5.1.0 - January 29th, 2019
- New features
- Git integration for plugins editor
- Import code libraries from Git
- More code reuse capabilities
- Prepare recipe in-database (SQL)
- Lightning-fast prepare recipe on Spark
- Containerized execution of notebooks
- GDPR capabilities
- Databricks
- Web apps as plugins
- Use Dataiku libs and develop code outside of DSS
- Folding the Flow view
- External hosting of runtime databases
- Exporting the Flow as an image
- Probability calibration
- Models export as PMML and POJO
- Duplicate projects
- RStudio integration
- Other notable enhancements
- Copy-paste preparation steps
- Copy-paste scenario steps
- Support for CDH 6
- New capabilities for Snowflake
- Setting distribution / primary index on Teradata, Redshift and Greenplum
- Support for impersonation on Teradata
- Support for custom query banding on Teradata
- More ability to use remote Git repositories
- More graceful handling of wide SQL tables
- Per-project libraries for R
- New Jobs UI
- New APIs
- Java 11
- Other enhancements and fixes
- New features
- DSS 5.0 Release notes
- DSS 4.3 Release notes
- DSS 4.2 Release notes
- DSS 4.1 Release notes
- Migration notes
- Version 4.1.5 - February, 13th 2018
- Version 4.1.4 - February, 8th 2018
- Version 4.1.3 - January, 8th 2018
- Version 4.1.2 - December, 12th 2017
- Version 4.1.1 - November, 20th 2017
- Version 4.1.0 - November, 13th 2017
- New features
- For coders: Multiple code environments for Python and R
- For coders: Python 3 support
- For coders: Shiny and Bokeh
- Mass actions and view on the Flow
- Filtering on the Flow
- For coders: RMarkdown
- For coders: custom charts on the dashboard
- For data scientists: Auto-ML features
- For data scientists: Grid search in MLLib models
- For data scientists: Ensemble models
- For analysts: Pivot recipe
- For analysts: Sort recipe
- For analysts: New “Split” recipe
- For analysts: Distinct recipe
- For analysts: “Top N” recipe
- R models in API node
- Arbitrary Python or R functions in the API node
- SQL queries in the API node
- Datasets lookup in the API node
- Index external tables in DSS catalog
- Folders and uploads everywhere
- New HTTP / FTP / SCP / SFTP support
- New chart features
- Attach more things to scenario emails
- Other notable enhancements
- Edit recipes in notebook
- Code editor enhancements
- Managed folder browser
- Plugin and libraries editor
- Plugin edition for non-administrators
- Spark 2.2
- SQL code formatter
- “Concat” aggregates in grouping and window recipes
- Better support for empty datasets
- Native TDCH support
- Plugins
- Misc (datasets)
- Misc (webapps)
- Misc (recipes)
- Misc (charts)
- Misc (data preparation)
- Misc (administration)
- Notable bug fixes
- New features
- DSS 4.0 Release notes
- Migration notes
- Version 4.0.9 - October, 3rd 2017
- Version 4.0.8 - September, 6th 2017
- Version 4.0.7 - August, 24th 2017
- Version 4.0.6 - July, 19th 2017
- Version 4.0.5 - June, 22nd 2017
- Version 4.0.4 - April, 27th 2017
- Version 4.0.3 - March, 27th 2017
- Version 4.0.2 - March, 1st 2017
- Version 4.0.1 - February, 16th 2017
- Version 4.0.0 - February, 13th 2017
- New features
- New dashboard
- Multi-user security
- Spark 2
- Spark pipelines
- Sparklyr
- Interactive hierarchical clustering
- Quick models
- Distributed and in-database scoring
- Notifications & Integrations
- New prebuilt notebooks
- Sort in explore
- Analyze on whole dataset in explore
- New data sources
- Audit trail
- Macros
- Sample and prepare memory limits
- Other notable enhancements
- Notable bug fixes
- New features
- DSS 3.1 Release notes
- DSS 3.0 Relase notes
- DSS 2.3 Relase notes
- DSS 2.2 Relase notes
- DSS 2.1 Relase notes
- DSS 2.0 Relase notes
- DSS 1.4 Relase notes
- DSS 1.3 Relase notes
- DSS 1.2 Relase notes
- DSS 1.1 Release notes
- DSS 1.0 Release Notes
- Pre versions