Claude Code dfd1a76978 ci: schedule a weekly Docker image rebuild against the latest release
Adds a cron-triggered workflow that re-runs the Docker image build
against the most-recent published release every Monday at 06:00 UTC
(and on manual workflow_dispatch when an operator wants to force it).
The Superset code being built doesn't change — but the base image
layers (python:*-slim-trixie and the Debian OS packages underneath)
DO receive upstream security patches between Superset releases. Without
a rebuild, apache/superset:<latest> ships those CVEs unfixed for as
long as the inter-release gap (typically 3–6 weeks).

Why this approach over the alternatives:

- Tied to releases: defeats the purpose — the gap we're trying to close
  IS the inter-release window. Release-triggered rebuilds happen exactly
  when we already get them.
- Swap to Chainguard / distroless: would also close the gap, but at the
  cost of a backward-incompatible package-manager change for downstream
  operators who extend `apache/superset:<tag>` with their own apt
  install lines for custom drivers. A scheduled rebuild captures most
  of the CVE-cycling benefit without that breakage.
- Daily cadence: probably overkill — Debian's security tree updates on
  a roughly weekly rhythm and a daily rebuild would just churn the
  registry without adding much.

Implementation: deliberately reuses the same `supersetbot docker`
invocation as `tag-release.yml` (same matrix of build presets, same
`--context release --context-ref <tag> --force-latest` flags), so the
resulting tags are byte-equivalent to what a manual release dispatch
would produce — only the base layer changes. Concurrency group
shared with the release publisher so the two can't race each other
on the Docker Hub push.

Tag mutability note: the rebuild overwrites both the rolling tags
(`apache/superset:latest`) AND the version-specific tag of the latest
release (e.g. `apache/superset:5.0.0`). This is intentional and
matches how the upstream `python:*-slim-trixie` images themselves
behave — version tags reflect content + latest patches, not a frozen
SHA. Users who need a frozen reference should pin by image digest.
2026-06-10 16:17:35 -07:00
2024-04-15 11:21:42 -06:00

Superset

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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

Repo Activity

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