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What is Preset?

In just a few simple clicks, you can effortlessly create and distribute dynamic, customizable, and visually appealing dashboards that effectively present your data. Utilize our no-code visualizer to explore your data or delve deeper with the advanced SQL editor for comprehensive analysis. The lightweight yet powerful visualization layer empowers you to maximize the value of your data infrastructure investments. Superset operates independently of any additional ingestion layers and is not tied to your underlying data architecture. Originally developed by Airbnb, Apache Superset is an open-source tool for data visualization. Preset, founded by the original creator and maintainer of Superset, offers a complete, user-friendly, enterprise-ready platform that enhances the capabilities of Superset significantly. This platform not only streamlines the data visualization process but also ensures that users can easily adapt it to their specific needs.

What is Apache Superset?

Superset is a powerful and intuitive platform filled with functionalities that enhance data exploration and visualization for users of all expertise levels, supporting a wide range of representations from simple line charts to complex geospatial visualizations. It can connect to any SQL-compatible data source through SQLAlchemy, making it adaptable to modern cloud-native databases and systems that manage massive volumes of petabyte-scale data. Furthermore, Superset's lightweight design and scalability enable it to leverage existing data infrastructure efficiently, negating the necessity for an additional layer of data ingestion. This characteristic positions it as an exceptional option for organizations aiming to optimize their data analytics capabilities effortlessly. Ultimately, Superset’s versatility and user-friendliness make it a valuable asset for businesses striving to enhance their insights through data.

Media

Media

Integrations Supported

Amazon Redshift
Apache Druid
Apache Kylin
ClickHouse
Dremio
Exasol
Google Cloud BigQuery
Greenplum
IBM Db2
MonetDB
MySQL
PostgreSQL
Presto
SQL Server
SQLite
Snowflake
DataHub
Gravity Data
Satori

Integrations Supported

Amazon Redshift
Apache Druid
Apache Kylin
ClickHouse
Dremio
Exasol
Google Cloud BigQuery
Greenplum
IBM Db2
MonetDB
MySQL
PostgreSQL
Presto
SQL Server
SQLite
Snowflake
DataHub
Gravity Data
Satori

API Availability

Has API

API Availability

Has API

Pricing Information

$25/month/user
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
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

Preset

Date Founded

2019

Company Location

United States

Company Website

preset.io

Company Facts

Organization Name

Apache

Date Founded

1999

Company Location

United States

Company Website

superset.apache.org

Categories and Features

Business Intelligence

Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics

Dashboard

Annotations
Data Source Integrations
Functions / Calculations
Interactive
KPIs
OLAP
Private Dashboards
Public Dashboards
Scorecards
Themes
Visual Analytics
Widgets

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Categories and Features

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

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