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Average Ratings 0 Ratings

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features
design
support

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Write a Review

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

Numerous products are available that assist businesses in this endeavor, but if your main goals are to build a data-driven organization while maximizing efficiency and minimizing costs, the only option worth considering is Fraxses, the leading distributed data platform in the world. Fraxses gives clients on-demand access to data, providing impactful insights through a solution that supports either a data mesh or data fabric architecture. Imagine a data mesh as a framework that overlays various data sources, linking them together and allowing them to operate as a cohesive unit. In contrast to other platforms focused on data integration and virtualization, Fraxses boasts a decentralized architecture that sets it apart. Although Fraxses is fully capable of accommodating traditional data integration methods, the future is leaning towards a novel approach where data is delivered directly to users, eliminating the necessity for a centrally managed data lake or platform. This innovative perspective not only enhances user autonomy but also streamlines data accessibility across the organization.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

APERIO DataWise Yes 
Airbyte Yes 
Amazon Web Services (AWS) Yes 
Apache Airflow Yes 
Apache Spark Yes 
Azure Databricks Yes 
Coginiti Yes 
Dask Yes 
DataHub Yes 
Google Cloud Platform Yes 
Great Expectations Yes 
Microsoft Azure Yes 
Microsoft Teams Yes 
OpenMetadata Yes 
PagerDuty Yes 
PostgreSQL Yes 
SDF Yes 
Snowflake Yes 
dbt Yes 
pandas Yes 

Integrations

APERIO DataWise No 
Airbyte No 
Amazon Web Services (AWS) No 
Apache Airflow No 
Apache Spark No 
Azure Databricks No 
Coginiti No 
Dask No 
DataHub No 
Google Cloud Platform No 
Great Expectations No 
Microsoft Azure No 
Microsoft Teams No 
OpenMetadata No 
PagerDuty No 
PostgreSQL No 
SDF No 
Snowflake No 
dbt No 
pandas 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 No 
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 No 
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 Yes 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

Dagster Labs

Founded

2019

Country

United States

Website

dagster.io

Vendor Details

Company Name

Intenda

Founded

2001

Country

South Africa

Website

intenda.tech/fraxses/

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

Data Fabric

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

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