Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
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
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
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
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