Hugh A Miles II eac1480eb6 fix(dashboard): address Excel export review feedback (timeouts, lock, boto3, image gating)
Addresses @EnxDev's review on #41133:

- Soft timeouts now abort the export instead of being caught per chart: the
  per-chart SoftTimeLimitExceeded handler (and screenshot.py's broad except)
  re-raise, so the outer handler emails a failure and runs cleanup rather than
  running to the hard limit (leaking temp files, holding the lock). Removes the
  now-dead ERROR_TIMEOUT reason.
- Concurrency guard uses a shared, atomic DistributedLock (Redis when
  configured, metadata DB otherwise) instead of cache_manager.cache, which is a
  no-op under the default NullCache and process-local under SimpleCache. The
  lock is released if apply_async fails so a broker outage can't block exports
  until the TTL expires.
- boto3 is declared via a new `excel-export` optional extra; superset.utils.s3
  raises an actionable install hint when it is missing.
- "Export Images to Excel" is gated on the webdriver screenshot feature flags
  (it renders via the headless webdriver); documents EXCEL_EXPORT_TABLE_VIZ_TYPES
  and the image mode in the config docs and UPDATING.md.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-13 11:28:20 -04:00

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 Athena   Amazon DynamoDB   Amazon Redshift   Apache Doris   Apache Drill   Apache Druid   Apache Hive   Apache Impala   Apache Kylin   Apache Pinot   Apache Solr   Apache Spark SQL   Ascend   Aurora MySQL (Data API)   Aurora PostgreSQL (Data API)   Azure Data Explorer   Azure Synapse   ClickHouse   Cloudflare D1   CockroachDB   Couchbase   CrateDB   Databend   Databricks   Denodo   Dremio   DuckDB   Elasticsearch   Exasol   Firebird   Firebolt   Google BigQuery   Google Sheets   Greenplum   Hologres   IBM Db2   IBM Netezza Performance Server   MariaDB   Microsoft SQL Server   MonetDB   MongoDB   MotherDuck   OceanBase   Oracle   Presto   RisingWave   SAP HANA   SAP Sybase   Shillelagh   SingleStore   Snowflake   SQLite   StarRocks   Superset meta database   TDengine   Teradata   TimescaleDB   Trino   Vertica   YDB   YugabyteDB

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

Languages
Python 38%
TypeScript 37.7%
Jupyter Notebook 21.3%
HTML 2.4%
JavaScript 0.3%
Other 0.2%