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Tech Ecosystem
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 Domino ProjectStep 3: Configure Your Domino 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 Domino Datasets
Domino Reference
Projects
Projects Overview
Revert Projects and Files
Revert a ProjectRevert a File
Projects PortfolioReference ProjectsProject Goals in Domino 4+
Git Integration
Git Repositories in DominoGit-based Projects with CodeSyncWorking from a Commit ID in Git
Jira Integration in DominoUpload Files to Domino using your BrowserFork and Merge ProjectsSearchSharing and CollaborationCommentsDomino Service FilesystemCompare File RevisionsArchive a Project
Advanced Project Settings
Project DependenciesProject TagsRename a ProjectSet up your Project to Ignore FilesUpload files larger than 550MBExporting Files as a Python or R PackageTransfer Project Ownership
Domino Runs
JobsDiagnostic Statistics with dominostats.jsonNotificationsResultsRun Comparison
Advanced Options for Domino Runs
Run StatesDomino Environment VariablesEnvironment Variables for Secure Credential StorageUse Apache Airflow with Domino
Scheduled Jobs
Domino Workspaces
WorkspacesUse Git in Your WorkspaceRecreate A Workspace From A Previous CommitUse Visual Studio Code in Domino WorkspacesPersist RStudio PreferencesAccess Multiple Hosted Applications in one Workspace Session
Spark on Domino
On-Demand Spark
On-Demand Spark OverviewValidated Spark VersionConfigure PrerequisitesWork with your ClusterManage DependenciesWork with Data
External Hadoop and Spark
Hadoop and Spark OverviewConnect 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 Ray
On-Demand Ray OverviewValidated Ray VersionConfigure PrerequisitesWork with your ClusterManage DependenciesWork with Data
On-Demand Dask
On-Demand Dask OverviewValidated Dask VersionConfigure PrerequisitesWork with Your ClusterManage DependenciesWork with Data
Customize the Domino Software Environment
Environment ManagementDomino Standard EnvironmentsInstall Packages and DependenciesAdd Workspace IDEsAdding Jupyter Kernels
Partner Environments for Domino
Use MATLAB as a WorkspaceUse Stata as a WorkspaceUse SAS as a WorkspaceNVIDIA NGC Containers
Advanced Options for Domino Software Environment
Install Custom Packages in Domino with Git IntegrationAdd Custom DNS Servers to Your Domino EnvironmentConfigure a Compute Environment to User Private Cran/Conda/PyPi MirrorsUse TensorBoard in Jupyter Workspaces
Publish your Work
Publish a Model API
Model Publishing OverviewModel Invocation SettingsModel Access and CollaborationModel Deployment ConfigurationPromote Projects to ProductionExport Model Image
Publish a Web Application
App Publishing OverviewGet Started with DashGet Started with ShinyGet Started with FlaskContent Security Policies for Web Apps
Advanced Web Application Settings in Domino
App Scaling and PerformanceHost HTML Pages from DominoHow to Get the Domino Username of an App Viewer
Launchers
Launchers OverviewAdvanced Launcher Editor
Assets Portfolio Overview
Model Monitoring and Remediation
Monitor WorkflowsData Drift and Quality Monitoring
Set up Monitoring for Model APIs
Set up Prediction CaptureSet up Drift DetectionSet up Model Quality MonitoringSet up NotificationsSet Scheduled ChecksSet up Cohort Analysis
Set up Model Monitor
Connect a Data SourceRegister a ModelSet up Drift DetectionSet up Model Quality MonitoringSet up Cohort AnalysisSet up NotificationsSet Scheduled ChecksUnregister a Model
Use Monitoring
Access the Monitor DashboardAnalyze Data DriftAnalyze Model QualityExclude Features from Scheduled Checks
Remediation
Cohort Analysis
Review the Cohort Analysis
Remediate a Model API
Monitor Settings
API TokenHealth DashboardNotification ChannelsTest Defaults
Monitoring Config JSON
Supported Binning Methods
Model Monitoring APIsTroubleshoot the Model Monitor
Connect to your Data
Data in Domino
Datasets OverviewProject FilesDatasets Best Practices
Connect to Data Sources
External Data VolumesDomino Data Sources
Connect to External Data
Connect Domino to DataRobotConnect to Amazon S3 from DominoConnect to BigQuery from DominoConnect to Generic S3 from DominoConnect to IBM DB2 from DominoConnect to IBM Netezza from DominoConnect to Impala from DominoConnect to MSSQL from DominoConnect to MySQL from DominoConnect to Okera from DominoConnect to Oracle Database from DominoConnect to PostgreSQL from DominoConnect to Redshift from DominoConnect to Snowflake from DominoConnect to Teradata from Domino
Work with Data Best Practices
Work with Big Data in DominoWork with Lots of FilesMove Data Over a Network
Advanced User Configuration Settings
User API KeysDomino TokenOrganizations Overview
Use the Domino Command Line Interface (CLI)
Install the Domino Command Line (CLI)Domino CLI ReferenceDownload Files with the CLIForce-Restore a Local ProjectMove a Project Between Domino DeploymentsUse the Domino CLI Behind a Proxy
Browser Support
Get Help with Domino
Additional ResourcesGet Domino VersionContact Domino Technical SupportSupport Bundles
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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-domino5.0

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Domino Minimal Environment (DME)

quay.io/domino/minimal-environment:ubuntu18-py3.8-domino5.0

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Domino Spark Environment

quay.io/domino/spark-environment:ubuntu18-py3.8-r4.1-spark3.1.2-hadoop3.2.0-domino5.0

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Domino Ray Environment

quay.io/domino/ray-environment:ubuntu18-py3.8-r4.1-ray1.6.0-domino5.0

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Domino Dask Environment

quay.io/domino/dask-environment:ubuntu18-py3.8-r4.1-dask2021.10.0-domino5.0

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

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CUDA 11 NGC Container (Domino enhanced)

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

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CUDA 10 NGC Container (Domino enhanced)

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

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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

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RAPIDS NGC Container (Domino enhanced)

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

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MXNET NGC Container (Domino enhanced)

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

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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

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

Getting started with Flask in Domino

shiny

Getting started with Shiny in Domino

dash

Getting started with Dash in Domino

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. Find instructions for publishing here.

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

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