72a7e06dd8
Prep work for the SQLAlchemy 1.4 -> 2.0 core bump (discussion #40273, step 6). Every SQLAlchemy-dependent package Superset ships or offers as an optional extra gets bumped to the newest release that supports both SQLAlchemy 1.4 and 2.0, so each bump can be merged and tested independently under today's SQLAlchemy 1.4 pin before the core bump lands as its own final PR. - flask-sqlalchemy: pin explicitly (was purely transitive via flask-appbuilder, resolving to 2.5.1, 1.4-only) at >=3.0.5,<3.1, the last release before 3.1.0 drops 1.4 support. flask-appbuilder and marshmallow-sqlalchemy are already dual-compatible as pinned, no change needed. - sqlalchemy-bigquery: 1.17.0 -> 1.17.1 (patch; the project was archived 2026-05-16, likely its final release). - sqlalchemy-cratedb: 0.41.0 -> 0.43.1. - sqlalchemy-drill: drop an artificial <2 SQLAlchemy-version ceiling upstream never had (1.1.10 already supports 2.0 via import_dbapi). - firebolt-sqlalchemy: 1.0.0 -> 1.1.2. - sqlalchemy-ocient: 1.0.0 -> 3.0.0 (lower confidence: closed-source vendor package, no public changelog to verify against). - snowflake-sqlalchemy floor was already bumped independently by dependabot (#42418) to the same target this research landed on. Five extras (risingwave, exasol, firebird, redshift, dremio) have NO release supporting both SQLAlchemy versions -- version numbers cut straight from 1.4-only to 2.0-only with no overlap. Pinned each to its last 1.4-only version with a comment noting the 2.0 target to bump to once the core sqlalchemy bump lands, not before. Four extras have no SQLAlchemy 2.0 support anywhere in their ecosystem today and are flagged via a new `known_incompatibilities` metadata field (surfaced through the generated database docs): kusto, aurora-data-api (including our own dormant preset-io fork), solr, and d1. sqlalchemy-vertica-python was initially suspected to be a fifth, but turned out to already be dual-compatible (v0.6.3 already ships `import_dbapi`/`text()` wrapping) once the actual merged PR was checked instead of relying on PyPI metadata alone. Verified locally: full dependency resolution succeeds, the app boots and creates all tables cleanly under SQLAlchemy 1.4.54 + Flask-SQLAlchemy 3.0.5, 483/487 relevant unit tests pass (the 4 failures are a pre-existing local mysqlclient linkage issue, unrelated to this change), and the new metadata flows through generate_yaml_docs() end-to-end for all four flagged engines.
Superset
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
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:
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
- Ask and answer questions on StackOverflow using the apache-superset tag
- Join our community's Slack and please read our Slack Community Guidelines
- Join our dev@superset.apache.org Mailing list. To join, simply send an email to dev-subscribe@superset.apache.org
- Follow us on social media: X | LinkedIn | Bluesky | Reddit
- If you want to help troubleshoot GitHub Issues involving the numerous database drivers that Superset supports, please consider adding your name and the databases you have access to on the Superset Database Familiarity Rolodex
- Join Superset's Town Hall and Operational Model recurring meetings. Meeting info is available on the Superset Community Calendar
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
- Superset "In the Wild" - see who's using Superset, and add your organization to the list!
- Feature Flags - the status of Superset's Feature Flags.
- Standard Roles - How RBAC permissions map to roles.
- Superset Wiki - Tons of additional community resources: best practices, community content and other information.
- Superset SIPs - The status of Superset's SIPs (Superset Improvement Proposals) for both consensus and implementation status.
Understanding the Superset Points of View
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Getting Started with Superset
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Deploying Superset
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Recordings of Past Superset Community Events
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Visualizations
