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Tech Ecosystem
Get Started
Get started with Python
Step 0: Orient yourself to DominoStep 1: Create a projectStep 2: Configure your projectStep 3: Start a workspaceStep 4: Get your files and dataStep 5: Develop your modelStep 6: Clean up WorkspacesStep 7: Deploy your model
Get started with R
Step 0: Orient yourself to Domino (R Tutorial)Step 1: Create a projectStep 2: Configure your projectStep 3: Start a workspaceStep 4: Get your files and dataStep 5: Develop your modelStep 6: Clean up WorkspacesStep 7: Deploy your model
Get Started with MATLAB
Step 1: Orient yourself to DominoStep 2: Create a ProjectStep 3: Configure Your ProjectStep 4: Start a MATLAB WorkspaceStep 5: Fetch and Save Your DataStep 6: Develop Your ModelStep 7: Clean Up Your Workspace
Step 8: Deploy Your Model
Scheduled JobsLaunchers
Step 9: Working with Datasets
Domino Reference Projects
Search in Deployments
Security and Credentials
Secure Credential Storage
Store Project CredentialsStore User CredentialsStore Model Credentials
Get API KeyUse a Token for AuthenticationCreate a Mirror of Compute Environments
Collaborate
Share and Collaborate on Projects
Set Project VisibilityInvite CollaboratorsCollaborator Permissions
Add Comments
Reuse Work
Set Up ExportsSet Up Imports
Organizations
Organization PermissionsTransfer Projects to an Organization
Projects
Domino File System Projects
Domino File SystemOrganize Domino File System Project AssetsImport Git RepositoriesWork from a Commit ID in GitCopy a ProjectFork ProjectsMerge Projects
Manage Project Files
Upload Files to DominoCompare File RevisionsExclude Project Files From SyncExport Files as Python or R Package
Archive a Project
Revert Projects and Files
Revert a FileRevert a Project
Git-based Projects
Git-based Project Directory StructureCreate a Git-based ProjectCreate a New RepositoryOrganize Git-based Project AssetsDevelop Models in a WorkspaceSave Artifacts to the Domino File System
Project FilesSet Project SettingsStore Project Credentials
Project Goals
Add GoalsEdit GoalsLink Work to Goals
Organize Projects with TagsSet Project Stages
Project Status
Set Project as BlockedSet Project as CompleteSet Project as Unblocked
View Execution DetailsView Project ActivityTrack Project StatusRename a Project
Share and Collaborate
Set Project VisibilityInvite CollaboratorsCollaborator Permissions
Export and Import Project Content
Set Up ExportsSet Up Imports
See the Assets for Your ProjectPromote Projects to ProductionTransfer Project OwnershipIntegrate Jira
Domino Datasets
Manage Large DataDatasets Best PracticesCreate a DatasetUse an Existing DatasetFile Location of Datasets in Projects
Datasets and Snapshots
Update a DatasetAdd Tags to SnapshotsCreate a Snapshot of a DatasetDelete Snapshots of DatasetsDelete a Dataset
Upgrade from Versions Prior to 4.5
External Data
Considerations for Connecting to Data Sources
External Data Volumes
Mount an External VolumeView Mounted VolumesUse a Mounted VolumeUmount a Volume
Tips: Transfer Data Over a Network
Workspaces
Create a Workspace
Open a VS Code WorkspaceSet Custom Preferences for RStudio Workspaces
Workspace Settings
Edit Workspace SettingsChange Your Workspace's Volume SizeConfigure Long-Running Workspaces
Save Work in a WorkspaceSync ChangesView WorkspacesStop a WorkspaceResume a WorkspaceDelete a WorkspaceView Workspace LogsView Workspace UsageView Workspace HistoryWork with Legacy Workspaces
Use Git in Your Workspace
Commit and Push Changes to Your Git RepositoryCommit All Changes to Your Git RepositoryPull the Latest Changes from Your Git Repository
Run Multiple Applications in a Workspace
Clusters
Spark on Domino
Hadoop and Spark Overview
Connect to a Cloudera CDH5 cluster from DominoConnect to a Hortonworks cluster from DominoConnect to a MapR cluster from DominoConnect to an Amazon EMR cluster from DominoRun Local Spark on a Domino ExecutorUse PySpark in Jupyter WorkspacesKerberos Authentication
On-Demand Spark Overview
Validated Spark VersionConfigure PrerequisitesWork with your ClusterManage DependenciesWork with Data
On-Demand Ray Overview
Validated Ray VersionConfigure PrerequisitesWork with your ClusterManage DependenciesWork with Data
On-Demand Dask Overview
Validated Dask VersionConfigure PrerequisitesWork with Your ClusterManage DependenciesWork with Data
Environments
Set a Default EnvironmentCreate an EnvironmentEdit Environment DefinitionView Your EnvironmentsView Environment RevisionsDuplicate an EnvironmentArchive an Environment
Environments
Example: Create a New Environment
Customize Environments
Install Custom Packages with Git Integration
Add Packages to Environments
Use Dockerfile InstructionsUse requirements.txt (Python only)Use the Execution to Add a Package
Add Workspace IDEsAdd a Scala KernelAccess Additional Domains and HostnamesUse TensorBoard in Jupyter Workspaces
Use Partner Environments
Use MATLAB as a WorkspaceUse Stata as a WorkspaceAdd an NVIDIA NGC to DominoUse SAS as a Workspace
Executions
Execution StatesDomino Environment Variables
Jobs
Start a JobScheduled Jobs
Launchers
Launchers OverviewCreate a LauncherRun a LauncherCopy Launcher Definitions
View Job DetailsCompare JobsTag JobsStop JobsView Execution Performance
Execution Notifications
Set Notification PreferencesSet Custom Execution Notifications
Execution Results
Download Execution ResultsCustomize the Results DashboardAutomate Complex Pipelines with Apache Airflow
Model APIs
Configure a Model for Deployment
Scale Models
Scale Python ModelsScale Model Versions
Configure Compute ResourcesRoute Your ModelProject Files in ModelsEnvironments for ModelsShare and Collaborate on Models
Publish
Model APIs
Publish a ModelSend Test Calls to the ModelPublish a New Version of a ModelSelect How to Authorize a Model
Domino Apps
Publish a Domino AppHost HTML Pages from DominoGrant Access to Domino AppsView a Domino AppView All Domino AppsIdentify Resources to WhitelistPublish a Python App with DashPublish an R App with ShinyPublish a Project as a Website with FlaskOptimize App Scalability and PerformanceGet the Domino Username of an App Viewer
Launchers
Create a LauncherRun a LauncherCopy Launcher Definitions
Model Monitoring
Model Monitoring APIsAccessing The Model MonitorGet Started with Model MonitoringModel Monitor DeploymentIngest Data into The Model MonitorModel RegistrationMonitoring Data DriftMonitoring Model QualitySetting Scheduled Checks for the ModelConfigure Notification Channels for the ModelUse Model Monitoring APIsProduct Settings
Domino Command Line Interface (CLI)
Install the Domino Command Line Interface (CLI)Domino CLI ReferenceDownload Files with the CLIForce-Restore a Local ProjectMove a Project Between DeploymentsUse the Domino CLI Behind a Proxy
Troubleshooting
Troubleshoot Domino ModelsWork with Many FilesTroubleshoot Imports
Get Help
Additional ResourcesGet Domino VersionContact Technical SupportSupport BundlesBrowser SupportUser Guide Updates
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Tech Ecosystem

Tech Ecosystem

Domino is an open enterprise platform for data science, machine learning, and AI research. It works with an expansive list of industry leading tools and technologies to enrich data science research, development, and deployment processes. Domino works with a wide range of data sources, languages, IDEs, tools, libraries, and publication targets, including:

  • Certified partners who have worked with Domino to integrate and verify their tools.

  • Other third-party tools and technologies known to work with Domino.

  • Access to other tools and technologies through code-first APIs or connections.

The catalog lists the integrations alphabetically and groups them according to the categories shown in the diagram.

Contact Domino Support if something is missing because we’re always adding new integrations and want to hear what’s top of mind for data scientists.

Domino is at the center of the machine learning ecosystem

Compute Environment Catalog

Domino is an open platform for data science which integrates various languages, IDEs, data sources, and tools in one place.

Domino pre-builds compute environments with partner technologies to make it easy for you to use the tools you want in your Domino installation. We build, test, and security scan the environments. Domino updates them periodically to keep the libraries and tools near their latest stable versions.

This topic includes a catalog of the environments. These can be pulled into any Domino installation which has access to quay.io. The URL provides the repo access to pull the image from and the linked documentation provides details on configuring those environments.

Note
PartnerProduct/Version

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Domino Standard Environment (DSE)

quay.io/domino/standard-environment:ubuntu18-py3.8-r4.1-domino4.6

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Domino Minimal Environment (DME)

quay.io/domino/minimal-environment:ubuntu18-py3.8-domino4.6

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Domino Spark Environment

quay.io/domino/spark-environment:ubuntu18-py3.8-r4.1-domino4.6

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Domino Ray Environment

quay.io/domino/ray-environment:ubuntu18-py3.8-r4.1-domino4.6

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Domino Dask Environment

quay.io/domino/dask-environment:ubuntu18-py3.8-r4.1-domino4.6

anaconda

Domino Analytics Distribution w/Anaconda

quay.io/domino/anaconda:latest

matlab

MATLAB 2021a

quay.io/domino/matlab:R2021a

matlab

MATLAB 2020b

quay.io/domino/matlab:R2020b

matlab

MATLAB 2020a

quay.io/domino/matlab:R2020a

matlab

MATLAB 2019b

quay.io/domino/matlab:R2019b

nvidia ngc

CUDA 11 NGC Container (Domino enhanced)

quay.io/domino/ngc-cuda:11.2.1-cudnn8-runtime-ubuntu20.04

nvidia ngc

CUDA 10 NGC Container (Domino enhanced)

quay.io/domino/ngc-cuda:10.2-cudnn8-runtime-ubuntu18.04

nvidia ngc

PyTorch NGC Container (Domino enhanced)

quay.io/domino/ngc-pytorch:20.12-py3

nvidia ngc

TensorFlow NGC Container (Domino enhanced)

quay.io/domino/ngc-tensorflow:20.12-tf1-py3

nvidia ngc

RAPIDS NGC Container (Domino enhanced)

quay.io/domino/ngc-rapids:0.18-cuda11.0-runtime-ubuntu20.04-py3.8

nvidia ngc

MXNET NGC Container (Domino enhanced)

quay.io/domino/ngc-mxnet:20.12-py3

nvidia ngc

Clara Train NGC Container (Domino enhanced)

quay.io/domino/ngc-clara-train:v3.1.01

nvidia ngc

Deepstream NGC Container (Domino enhanced)

quay.io/domino/ngc-deepstream:5.1-21.02-devel

snowflake

Snowflake Snowpark Scala

quay.io/domino/snowflake:snowpark-scala-latest

sas

SAS Analytics Pro

quay.io/domino/sas:apro-latest

sas

SAS Analytics Pro

quay.io/domino/sas:sasds-latest

sas

SAS Analytics Pro

quay.io/domino/sas:sa4c94-latest

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Stata 17

quay.io/domino/stata:17

Data sources

SolutionPartnerIntegration information

snowflake

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Connecting to Snowflake from Domino

awss3

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Connecting to S3 from Domino

awsredshift

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Connecting to Redshift from Domino

palantir

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Connecting to Palantir Foundry from Domino

teradata150

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Connecting to Teradata from Domino

postgresql

Connecting to PostgreSQL from Domino

mssqlserver

Connecting to Microsoft SQL Server from Domino

impala

Connecting to Impala from Domino

oracle

Connecting to Oracle DB from Domino

mysql

Connecting to MySQL from Domino

Data governance

SolutionPartnerIntegration information

okera

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Connecting to Okera from Domino

Tools & IDEs

SolutionPartnerIntegration information

rstudio

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RStudio comes standard in the Domino Analytics Distribution

jupyter

Jupyter and JupyterLab come standard in the Domino Analytics Distribution

matlab

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Domino distributes a base MATLAB environment image which you can add as a Workspace

sas

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Use your SAS Viya Data Science Studio in Domino. Learn how to create a SAS Workspace Environment

stata logo blue

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Domino distributes a base Stata environment image which you can add as a Workspace

visualstudio

Using Visual Studio Code in Domino

zeppelin

How to set up Zeppelin Workspaces in Domino

Packages & libraries

SolutionPartnerIntegration information

anaconda

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Miniconda can be added to Domino environments and you can specify a local mirror.

h2o

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Install H2O

datarobot

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Connecting to DataRobot in Domino

Spark & Hadoop clusters

SolutionPartnerIntegration information

cloudera

Connecting to a Cloudera CDH5 cluster from Domino

hortonworks

Connecting to a Hortonworks cluster from Domino

mapr

Connecting to a MapR cluster from Domino

awsemr

Connecting to an Amazon EMR cluster from Domino

App frameworks

SolutionPartnerIntegration information

flask

Publish a Project as a Website with Flask

shiny

Publish an R App with Shiny

dash

Publish a Python App with Dash

django

Getting started with Django in Domino

Model publishing

SolutionPartnerIntegration information

sagemaker

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With Domino you can export a model endpoint which is compatible with AWS Sagemaker. See What Is Amazon SageMaker? for how to publish.

If you are a partner interested in certifying your solution in Domino, contact partners@dominodatalab.com.

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