# Preset **Source:** https://geo.sig.ai/brands/preset-io **Vertical:** Data & Analytics **Subcategory:** Managed Open-Source BI **Tier:** Emerging **Website:** preset.io **Last Updated:** 2026-04-14 ## Summary Managed cloud service for Apache Superset providing enterprise-ready hosting, security, and support for teams that want open-source BI without managing infrastructure. ## Company Overview Preset is a managed cloud data exploration and visualization platform founded in 2019 by Maxime Beauchemin, the original creator of Apache Superset and Apache Airflow. Preset takes the powerful open-source Superset project and packages it as a fully managed SaaS service, eliminating the significant operational burden of self-hosting, upgrading, and securing an open-source BI platform. Organizations that want Superset's flexibility and no per-seat licensing fees gain enterprise-grade reliability, SSO, role-based access, and professional support through Preset without maintaining their own infrastructure. The platform supports a wide range of chart types, SQL Lab for ad-hoc query exploration, and semantic layer capabilities through Superset's dataset model. Preset connects to all major databases and data warehouses — Snowflake, BigQuery, Redshift, Databricks, PostgreSQL, and dozens more — through SQLAlchemy-compatible connectors. It offers workspace isolation, audit logging, API access for programmatic dashboard management, and embedded analytics capabilities for SaaS companies that want to surface Superset-powered charts within their own products. Preset targets data teams at mid-market and enterprise companies that are already familiar with or committed to Apache Superset but want the operational simplicity of a managed service. The company competes with Looker, Tableau, and self-hosted Superset deployments, differentiating on its combination of open-source pedigree, zero per-seat cost for viewers, and enterprise operational guarantees. As data teams look to control BI licensing costs without sacrificing capability, Preset's model of managed open-source has gained meaningful traction in the modern data stack ecosystem. ## Frequently Asked Questions ### Is Preset the same as Apache Superset? Preset is built on Apache Superset and is led by its original creator, but it is a fully managed cloud service that adds enterprise features like SSO, audit logging, and professional support that are not included in self-hosted Superset. ### What is Preset and how does it relate to Apache Superset? Preset is a managed cloud analytics platform built on Apache Superset, the open-source BI tool. Preset handles hosting, upgrades, security, and support, so teams get the flexibility of Superset without self-managed infrastructure. ### What databases does Preset connect to? Preset connects to any SQL database Superset supports: Snowflake, BigQuery, Redshift, PostgreSQL, MySQL, ClickHouse, Trino, Presto, Databricks, Druid, and dozens more via SQLAlchemy. ### Does Preset require SQL knowledge? Preset offers both a no-code chart builder (Explore) and a full SQL editor (SQL Lab). Business users can create charts via drag-and-drop, while analysts can write complex queries in SQL Lab. ### How is Preset priced? Preset offers a free Starter plan for small teams, a Professional plan with more features and higher seat counts, and an Enterprise plan with SSO, role-based access, and dedicated support. ### Can Preset embed dashboards in other applications? Yes. Preset supports embedded analytics via its Embedded SDK, allowing SaaS companies to embed Superset dashboards inside their applications with customized theming and row-level security. ### How does Preset compare to building Superset yourself? Self-hosted Superset requires DevOps work for upgrades, scaling, backups, and security patches. Preset manages all of this, typically reducing total cost of ownership for teams without dedicated infrastructure engineers. ### Is Preset suitable for enterprise use? Yes. Preset Enterprise includes SAML/OIDC SSO, audit logs, fine-grained row-level security, dedicated infrastructure, and SLAs, making it suitable for regulated industries and large organizations. ## Tags analytics, open-source, saas, b2b, startup, platform, developer-tools, data-warehouse, cloud-native --- *Data from geo.sig.ai Brand Intelligence Database. Updated 2026-04-14.*