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แพลตฟอร์ม Business Intelligence สำหรับสำรวจข้อมูล สร้างกราฟ SQL และ dashboard แบบ interactive

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Superset

License Latest Release on Github Build Status PyPI version PyPI GitHub Stars Contributors Last Commit Open Issues Open PRs Get on Slack Documentation

Superset logo (light)

A modern, enterprise-ready business intelligence web application.

Documentation

  • User Guide — For analysts and business users. Explore data, build charts, create dashboards, and connect databases.
  • Administrator Guide — Install, configure, and operate Superset. Covers security, scaling, and database drivers.
  • Developer Guide — Contribute to Superset or build on its REST API and extension framework.

Why Superset? | Supported Databases | Release Notes | Get Involved | Resources | Organizations Using Superset

Why Superset?

Superset is a modern data exploration and data visualization platform. Superset can replace or augment proprietary business intelligence tools for many teams. Superset integrates well with a variety of data sources.

Superset provides:

  • A no-code interface for building charts quickly
  • A powerful, web-based SQL Editor for advanced querying
  • A lightweight semantic layer for quickly defining custom dimensions and metrics
  • Out of the box support for nearly any SQL database or data engine
  • A wide array of beautiful visualizations to showcase your data, ranging from simple bar charts to geospatial visualizations
  • Lightweight, configurable caching layer to help ease database load
  • Highly extensible security roles and authentication options
  • An API for programmatic customization
  • A cloud-native architecture designed from the ground up for scale

Screenshots & Gifs

Video Overview

superset-video-1080p.webm

Large Gallery of Visualizations

Craft Beautiful, Dynamic Dashboards

No-Code Chart Builder

Powerful SQL Editor

Supported Databases

Superset can query data from any SQL-speaking datastore or data engine (Presto, Trino, Athena, and more) that has a Python DB-API driver and a SQLAlchemy dialect.

Here are some of the major database solutions that are supported:

Amazon AthenaAmazon DynamoDBAmazon RedshiftApache DorisApache DrillApache DruidApache HiveApache ImpalaApache KylinApache PinotApache SolrApache Spark SQLAscendAurora MySQL (Data API)Aurora PostgreSQL (Data API)Azure Data ExplorerAzure SynapseClickHouseCloudflare D1CockroachDBCouchbaseCrateDBDatabendDatabricksDenodoDremioDuckDBElasticsearchExasolFirebirdFireboltGoogle BigQueryGoogle SheetsGreenplumHologresIBM Db2IBM Netezza Performance ServerMariaDBMicrosoft SQL ServerMonetDBMongoDBMotherDuckOceanBaseOraclePrestoRisingWaveSAP HANASAP SybaseShillelaghSingleStoreSnowflakeSQLiteStarRocksSuperset meta databaseTDengineTeradataTimescaleDBTrinoVerticaYDBYugabyteDB

A more comprehensive list of supported databases along with the configuration instructions can be found here.

Want to add support for your datastore or data engine? Read more here about the technical requirements.

Installation and Configuration

Try out Superset's quickstart guide or learn about the options for production deployments.

Get Involved

Contributor Guide

Interested in contributing? Check out our Developer Guide to find resources around contributing along with a detailed guide on how to set up a development environment.

Resources

Understanding the Superset Points of View

  • [The Case for Dataset-Centric Visualization](https://preset.io/blog/dataset-centric-visualization/)
  • [Understanding the Superset Semantic Layer](https://preset.io/blog/understanding-superset-semantic-layer/)
  • Getting Started with Superset- [Superset in 2 Minutes using Docker Compose](https://superset.apache.org/docs/installation/docker-compose#installing-superset-locally-using-docker-compose) - [Installing Database Drivers](https://superset.apache.org/docs/configuration/databases#installing-database-drivers) - [Building New Database Connectors](https://preset.io/blog/building-database-connector/) - [Create Your First Dashboard](https://superset.apache.org/docs/using-superset/creating-your-first-dashboard/) - [Comprehensive Tutorial for Contributing Code to Apache Superset ](https://preset.io/blog/tutorial-contributing-code-to-apache-superset/)
  • [Resources to master Superset by Preset](https://preset.io/resources/)
  • Deploying Superset - [Official Docker image](https://hub.docker.com/r/apache/superset) - [Helm Chart](https://github.com/apache/superset/tree/master/helm/superset)
  • Recordings of Past [Superset Community Events](https://preset.io/events) - [Mixed Time Series Charts](https://preset.io/events/mixed-time-series-visualization-in-superset-workshop/) - [How the Bing Team Customized Superset for the Internal Self-Serve Data & Analytics Platform](https://preset.io/events/how-the-bing-team-heavily-customized-superset-for-their-internal-data/) - [Live Demo: Visualizing MongoDB and Pinot Data using Trino](https://preset.io/events/2021-04-13-visualizing-mongodb-and-pinot-data-using-trino/) - [Introduction to the Superset API](https://preset.io/events/introduction-to-the-superset-api/) - [Building a Database Connector for Superset](https://preset.io/events/2021-02-16-building-a-database-connector-for-superset/)
  • Visualizations - [Creating Viz Plugins](https://superset.apache.org/docs/contributing/creating-viz-plugins/) - [Managing and Deploying Custom Viz Plugins](https://medium.com/nmc-techblog/apache-superset-manage-custom-viz-plugins-in-production-9fde1a708e55) - [Why Apache Superset is Betting on Apache ECharts](https://preset.io/blog/2021-4-1-why-echarts/)
  • [Superset API](https://superset.apache.org/docs/rest-api)
#analytics#apache#apache-superset#asf#bi#business-analytics#business-intelligence#data-analysis#data-analytics#data-engineering#data-science#data-visualization