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What is Veracity Data Fabric?

Veracity Data Fabric provides a secure platform for managing data across both cloud environments and on-premise infrastructures. It allows users to consolidate various types of information, such as data streams and individual data objects, with secure sharing capabilities that enhance usability. Users can choose to utilize their own data or seamlessly combine it with other datasets, providing them with complete autonomy over their choices. The platform is equipped with advanced security measures and grants access to a diverse range of data and analytics providers tailored for numerous sectors, which empowers users to dictate how and when they interact with these tools. Access permissions are effectively managed through SAS (shared access signature) keys, which give users the ability to control who can access their data. All actions related to the data stored within the container are meticulously recorded in a ledger, enabling container owners to track and review activities for added transparency. Moreover, these keys can only be shared with users who have been authenticated on the platform, ensuring that security and data integrity remain paramount. This thorough system not only allows users to retain control over their data but also encourages collaboration when it is beneficial. Ultimately, Veracity Data Fabric stands out as a comprehensive solution for data management, addressing both security and accessibility needs.

What is Dagster+?

Dagster serves as a cloud-native open-source orchestrator that streamlines the entire development lifecycle by offering integrated lineage and observability features, a declarative programming model, and exceptional testability. This platform has become the preferred option for data teams tasked with the creation, deployment, and monitoring of data assets. Utilizing Dagster allows users to concentrate on executing tasks while also pinpointing essential assets to develop through a declarative methodology. By adopting CI/CD best practices from the outset, teams can construct reusable components, identify data quality problems, and detect bugs in the early stages of development, ultimately enhancing the efficiency and reliability of their workflows. Consequently, Dagster empowers teams to maintain a high standard of quality and adaptability throughout the data lifecycle.

Media

Media

Integrations Supported

APERIO DataWise
Airbyte
Amazon Web Services (AWS)
Apache Spark
Azure Databricks
Coginiti
DataHub
Databricks Data Intelligence Platform
Datadog
GitHub
Google Cloud Platform
Great Expectations
Jupyter Notebook
Kubernetes
MLflow
Microsoft Teams
MySQL
PagerDuty
PostgreSQL
pandas

Integrations Supported

APERIO DataWise
Airbyte
Amazon Web Services (AWS)
Apache Spark
Azure Databricks
Coginiti
DataHub
Databricks Data Intelligence Platform
Datadog
GitHub
Google Cloud Platform
Great Expectations
Jupyter Notebook
Kubernetes
MLflow
Microsoft Teams
MySQL
PagerDuty
PostgreSQL
pandas

API Availability

Has API

API Availability

Has API

Pricing Information

€420 per year
Free Trial Offered?
Free Version

Pricing Information

$0
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Veracity

Company Location

Norway

Company Website

store.veracity.com/veracity-data-fabric-secure-data-sharing

Company Facts

Organization Name

Dagster Labs

Date Founded

2019

Company Location

United States

Company Website

dagster.io

Categories and Features

Data Fabric

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

Categories and Features

Data Fabric

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

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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