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features
design
support

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Write a Review

Description

Discover the reasons why leading companies are turning to the Crux external data automation platform to enhance their external data integration, transformation, and monitoring without the need for additional personnel. Our cloud-native technology streamlines the processes of ingesting, preparing, observing, and consistently delivering any external dataset. Consequently, this enables you to receive high-quality data precisely where and when you need it, formatted correctly. Utilize features such as automated schema detection, inferred delivery schedules, and lifecycle management to swiftly create pipelines from diverse external data sources. Moreover, boost data discoverability across your organization with a private catalog that links and matches various data products. Additionally, you can enrich, validate, and transform any dataset, allowing for seamless integration with other data sources, which ultimately speeds up your analytics processes. With these capabilities, your organization can fully leverage its data assets to drive informed decision-making and strategic growth.

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.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS) Yes 
Google Cloud Platform Yes 
Microsoft Azure Yes 
Snowflake Yes 
Airbyte No 
Amazon S3 Yes 
Collate No 
DataHub No 
Databricks No 
Datadog No 
Great Expectations No 
Kubernetes No 
MLflow No 
MySQL No 
OpenMetadata No 
PagerDuty No 
PostgreSQL No 
Tobiko No 
dbt No 
pandas No 

Integrations

Amazon Web Services (AWS) Yes 
Google Cloud Platform Yes 
Microsoft Azure Yes 
Snowflake Yes 
Airbyte Yes 
Amazon S3 No 
Collate Yes 
DataHub Yes 
Databricks Yes 
Datadog Yes 
Great Expectations Yes 
Kubernetes Yes 
MLflow Yes 
MySQL Yes 
OpenMetadata Yes 
PagerDuty Yes 
PostgreSQL Yes 
Tobiko Yes 
dbt Yes 
pandas Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version 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 

Deployment

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

Customer Support

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

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
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

Crux

Founded

2017

Country

United States

Website

www.cruxdata.com

Vendor Details

Company Name

Dagster Labs

Founded

2019

Country

United States

Website

dagster.io

Product Features

Big Data

Collaboration No 
Data Blends No 
Data Cleansing No 
Data Mining No 
Data Visualization No 
Data Warehousing No 
High Volume Processing No 
No-Code Sandbox No 
Predictive Analytics No 
Templates No 

Data Management

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

Data Quality

Address Validation No 
Data Deduplication No 
Data Discovery No 
Data Profililng No 
Master Data Management No 
Match & Merge No 
Metadata Management No 

ETL

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

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 

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