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features
design
support

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Description

Dagster is the cloud-native open-source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. It is the platform of choice data teams responsible for the development, production, and observation of data assets. With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early.

Description

Open core technology facilitates the integration of hybrid and multi-cloud environments. Built on the open-source initiative CDAP, Data Fusion guarantees portability of data pipelines for its users. The extensive compatibility of CDAP with both on-premises and public cloud services enables Cloud Data Fusion users to eliminate data silos and access previously unreachable insights. Additionally, its seamless integration with Google’s top-tier big data tools enhances the user experience. By leveraging Google Cloud, Data Fusion not only streamlines data security but also ensures that data is readily available for thorough analysis. Whether you are constructing a data lake utilizing Cloud Storage and Dataproc, transferring data into BigQuery for robust data warehousing, or transforming data for placement into a relational database like Cloud Spanner, the integration capabilities of Cloud Data Fusion promote swift and efficient development while allowing for rapid iteration. This comprehensive approach ultimately empowers businesses to derive greater value from their data assets.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Google Cloud Platform Yes 
APERIO DataWise Yes 
Amazon Web Services (AWS) Yes 
Apache Airflow Yes 
Azure Databricks Yes 
Coginiti Yes 
Dask Yes 
Google Cloud Datastream No 
Great Expectations Yes 
IntelliPay No 
Jupyter Notebook Yes 
Kubernetes Yes 
MLflow Yes 
Microsoft Azure Yes 
PagerDuty Yes 
Papertrail Yes 
PostgreSQL Yes 
SDF Yes 
Snowflake Yes 
dbt Yes 

Integrations

Google Cloud Platform Yes 
APERIO DataWise No 
Amazon Web Services (AWS) No 
Apache Airflow No 
Azure Databricks No 
Coginiti No 
Dask No 
Google Cloud Datastream Yes 
Great Expectations No 
IntelliPay Yes 
Jupyter Notebook No 
Kubernetes No 
MLflow No 
Microsoft Azure No 
PagerDuty No 
Papertrail No 
PostgreSQL No 
SDF No 
Snowflake No 
dbt No 

Pricing Details

$0
Pricing starts at $0.04/min for Serverless and $0.03/min for Hybrid, and tapers down from there based on usage.
Free Trial Yes 
Free Version Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Dagster Labs

Founded

2019

Country

United States

Website

dagster.io

Vendor Details

Company Name

Google

Country

United States

Website

cloud.google.com/data-fusion

Product Features

Data Fabric

Data Access Management No 
Data Analytics Yes 
Data Collaboration Yes 
Data Lineage Tools Yes 
Data Networking / Connecting Yes 
Metadata Functionality Yes 
No Data Redundancy No 
Persistent Data Management No 

Data Management

Customer Data No 
Data Analysis Yes 
Data Capture No 
Data Integration Yes 
Data Migration Yes 
Data Quality Control No 
Data Security No 
Information Governance No 
Master Data Management No 
Match & Merge Yes 

ETL

Data Analysis Yes 
Data Filtering Yes 
Data Quality Control No 
Job Scheduling Yes 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training Yes 
Natural Language Processing (NLP) No 
Predictive Modeling Yes 
Statistical / Mathematical Tools Yes 
Templates No 
Visualization No 

Product Features

ETL

Data Analysis Yes 
Data Filtering Yes 
Data Quality Control Yes 
Job Scheduling Yes 
Match & Merge Yes 
Metadata Management Yes 
Non-Relational Transformations No 
Version Control Yes 

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