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What is Gravity Data?

Gravity is designed to streamline the process of streaming data from more than 100 sources, ensuring that users only incur costs for what they actually use. It features a user-friendly interface that removes the necessity for engineering teams to build complex streaming pipelines, enabling quick setup from databases, event sources, and APIs in a matter of minutes. This capability allows everyone on the data team to work in an intuitive point-and-click environment, thereby focusing on creating applications, services, and improving customer interactions. Moreover, Gravity includes robust execution tracing and clear error messages, which assist in the rapid identification and resolution of issues that may arise. To support a fast onboarding process, we have rolled out numerous new functionalities, such as bulk setup options, predefined schemas, customizable data selection, as well as various job modes and statuses. With Gravity, you can allocate less time to infrastructure management and dedicate more time to data analysis, thanks to our smart engine that ensures your pipelines operate without interruption. In addition, Gravity seamlessly integrates with your current systems to facilitate effective notifications and orchestration, thus improving overall workflow productivity. Ultimately, Gravity provides your team with the essential tools to effortlessly convert data into actionable insights, fostering a more data-driven decision-making process. This holistic approach not only enhances efficiency but also empowers teams to harness the full potential of their data resources.

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

GitHub
MySQL
PostgreSQL
Slack
Snowflake
Twilio
Amazon Redshift
ClickUp
Eventbrite
Google Cloud BigQuery
Magento
Navisite DBaaS
Ortto
SQL Server
Shopify
Stripe
monday AI work platform

Integrations Supported

GitHub
MySQL
PostgreSQL
Slack
Snowflake
Twilio
Google Cloud Platform
Microsoft Teams

API Availability

API Availability

Has API

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

$0
Pricing starts at $0.04/min for Serverless and $0.03/min for Hybrid, and tapers down from there based on usage.
Free Version
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Gravity

Date Founded

2021

Company Location

United Kingdom

Company Website

gravitydata.co

Company Facts

Organization Name

Dagster Labs

Date Founded

2019

Company Location

United States

Company Website

dagster.io

Categories and Features

Data Pipeline

Not specified

ETL

Not specified

Categories and Features

Data Fabric

Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality

Data Management

Data Analysis
Data Integration
Data Migration
Match & Merge

Data Pipeline

Not specified

ETL

Data Analysis
Data Filtering
Job Scheduling

Machine Learning

Model Training
Predictive Modeling
Statistical / Mathematical Tools

ML Model Deployment

Not specified

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