Dagster 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.
Dagster Alternatives
Vertex AI
Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case.
Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection.
Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.
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RunPod
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Rivery
Rivery’s ETL platform consolidates, transforms, and manages all of a company’s internal and external data sources in the cloud.
Key Features:
Pre-built Data Models: Rivery comes with an extensive library of pre-built data models that enable data teams to instantly create powerful data pipelines.
Fully managed: A no-code, auto-scalable, and hassle-free platform. Rivery takes care of the back end, allowing teams to spend time on mission-critical priorities rather than maintenance.
Multiple Environments: Rivery enables teams to construct and clone custom environments for specific teams or projects.
Reverse ETL: Allows companies to automatically send data from cloud warehouses to business applications, marketing clouds, CPD’s, and more.
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dbt
Version control, quality assurance, documentation, and modularity enable data teams to work together similarly to software engineering teams. It is crucial to address analytics errors with the same urgency as one would for bugs in a live product. A significant portion of the analytic workflow is still performed manually. Therefore, we advocate for workflows to be designed for execution with a single command. Data teams leverage dbt to encapsulate business logic, making it readily available across the organization for various purposes including reporting, machine learning modeling, and operational tasks. The integration of continuous integration and continuous deployment (CI/CD) ensures that modifications to data models progress smoothly through the development, staging, and production phases. Additionally, dbt Cloud guarantees uptime and offers tailored service level agreements (SLAs) to meet organizational needs. This comprehensive approach fosters a culture of reliability and efficiency within data operations.
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Pricing
Pricing Starts At:
$0
Pricing Information:
Pricing starts at $0.04/min for Serverless and $0.03/min for Hybrid, and tapers down from there based on usage.
Free Version:
Yes
Free Trial:
Yes
Company Details
Company:
Dagster Labs
Year Founded:
2019
Headquarters:
United States
Website:
dagster.io
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Product Details
Platforms
Web-Based
Windows
Mac
Linux
On-Premises
Types of Training
Training Docs
Customer Support
Live Rep (24/7)
Online Support
Dagster Features and Options
Data Management Software
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Data Fabric Software
Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management
Machine Learning Software
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
ETL Software
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Dagster Lists
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