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Average Ratings 28 Ratings

Total
ease
features
design
support

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

Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence. Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs. Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500 companies, such as United, Kroger, Philips, Truist, and many others.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Databricks Yes 
GitHub Yes 
Apache Airflow Yes 
Apache Spark Yes 
Axis LMS No 
Azure Kubernetes Service (AKS) Yes 
Confluence No 
DataHub Yes 
Datadog Yes 
Google Cloud Platform Yes 
Great Expectations Yes 
IBM Rational ClearQuest No 
Kubernetes Yes 
MLflow Yes 
Meta Ads No 
Microsoft Azure Yes 
Microsoft Teams Yes 
Papertrail Yes 
Slack Yes 
Twilio Yes 

Integrations

Databricks Yes 
GitHub Yes 
Apache Airflow No 
Apache Spark No 
Axis LMS Yes 
Azure Kubernetes Service (AKS) No 
Confluence Yes 
DataHub No 
Datadog No 
Google Cloud Platform No 
Great Expectations No 
IBM Rational ClearQuest Yes 
Kubernetes No 
MLflow No 
Meta Ads Yes 
Microsoft Azure No 
Microsoft Teams No 
Papertrail No 
Slack No 
Twilio 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

$0.25/credit
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 Yes 
iPad App Yes 
Android App Yes 
Windows Yes 
Mac Yes 
Linux No 
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 No 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Dagster Labs

Founded

2019

Country

United States

Website

dagster.io

Vendor Details

Company Name

Gathr.ai

Country

United States

Website

www.gathr.ai

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 

Data Preparation

Collaboration Tools No 
Data Access No 
Data Blending No 
Data Cleansing No 
Data Governance No 
Data Mashup No 
Data Modeling No 
Data Transformation No 
Machine Learning No 
Visual User Interface No 

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports 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 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Streaming Analytics

Data Enrichment Yes 
Data Wrangling / Data Prep Yes 
Multiple Data Source Support Yes 
Process Automation Yes 
Real-time Analysis / Reporting Yes 
Visualization Dashboards Yes 

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